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48c56690f92f40911e5a2f43cd7eee0c0cab2587
|
# Dataset Card for "mmlu-high_school_mathematics-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-high_school_mathematics-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:49:27+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 8146, "num_examples": 5}, {"name": "test", "num_bytes": 2092208, "num_examples": 270}], "download_size": 223300, "dataset_size": 2100354}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:40:47+00:00
|
83f1bd182ac9c166431fa3bd33bb4c1b94e00fb4
|
# Dataset Card for "mmlu-high_school_microeconomics-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-high_school_microeconomics-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:49:36+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 6787, "num_examples": 5}, {"name": "test", "num_bytes": 1900343, "num_examples": 238}], "download_size": 209220, "dataset_size": 1907130}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:41:20+00:00
|
7cb6cb320bbf61099e831d0cdc023e0ef8a1c457
|
# Dataset Card for "mmlu-high_school_physics-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-high_school_physics-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:49:46+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 8534, "num_examples": 5}, {"name": "test", "num_bytes": 1413219, "num_examples": 151}], "download_size": 206264, "dataset_size": 1421753}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:41:52+00:00
|
7ee6ef97411105f04d1723855a83bdf2b1149083
|
# Dataset Card for "mmlu-high_school_psychology-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-high_school_psychology-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:50:06+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 9644, "num_examples": 5}, {"name": "test", "num_bytes": 6027159, "num_examples": 545}], "download_size": 475533, "dataset_size": 6036803}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:42:26+00:00
|
33af6f2e43b48a279514592147baf703f4571c64
|
# Dataset Card for "mmlu-high_school_statistics-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-high_school_statistics-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:50:15+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 10793, "num_examples": 5}, {"name": "test", "num_bytes": 2682018, "num_examples": 216}], "download_size": 270672, "dataset_size": 2692811}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:43:01+00:00
|
d0d9eb14c43354e2afaccb1c1c7fa463d55144dc
|
# Dataset Card for "mmlu-high_school_us_history-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-high_school_us_history-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:50:34+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 29801, "num_examples": 5}, {"name": "test", "num_bytes": 5547736, "num_examples": 204}], "download_size": 592013, "dataset_size": 5577537}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:43:34+00:00
|
6ddb347dce39fd504690321cea8b4159fbb49c74
|
# Dataset Card for "mmlu-high_school_world_history-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-high_school_world_history-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:50:44+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 19141, "num_examples": 5}, {"name": "test", "num_bytes": 5052971, "num_examples": 237}], "download_size": 730947, "dataset_size": 5072112}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:44:08+00:00
|
b94147b4047ee3a6167fb64eadb591faf3d87244
|
# Dataset Card for "mmlu-human_aging-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-human_aging-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:50:53+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 6169, "num_examples": 5}, {"name": "test", "num_bytes": 1367982, "num_examples": 223}], "download_size": 170997, "dataset_size": 1374151}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:44:40+00:00
|
360d78ecf8cbbc43e270fda56ad54f4b20a565ea
|
# Dataset Card for "mmlu-human_sexuality-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-human_sexuality-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:51:07+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 6330, "num_examples": 5}, {"name": "test", "num_bytes": 878404, "num_examples": 131}], "download_size": 144186, "dataset_size": 884734}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:45:10+00:00
|
b855f20fe199a0920a29b190880967b20a4102dc
|
# Dataset Card for "mmlu-international_law-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-international_law-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:51:16+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 10115, "num_examples": 5}, {"name": "test", "num_bytes": 1680951, "num_examples": 121}], "download_size": 145868, "dataset_size": 1691066}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:45:42+00:00
|
e48756ac783395c0fa9f4123b938fa2b76e78fca
|
# Dataset Card for "mmlu-jurisprudence-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-jurisprudence-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:51:34+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 7496, "num_examples": 5}, {"name": "test", "num_bytes": 924962, "num_examples": 108}], "download_size": 149794, "dataset_size": 932458}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:46:14+00:00
|
23569c4fa75521add1d25091ccc023a6e142ea9b
|
# Dataset Card for "mmlu-logical_fallacies-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-logical_fallacies-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:51:58+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 8002, "num_examples": 5}, {"name": "test", "num_bytes": 1526448, "num_examples": 163}], "download_size": 164600, "dataset_size": 1534450}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:46:43+00:00
|
a3bd6bd9686f04ce64209e456b185b48f9c4b17e
|
# Dataset Card for "mmlu-machine_learning-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-machine_learning-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:52:05+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 10794, "num_examples": 5}, {"name": "test", "num_bytes": 1393778, "num_examples": 112}], "download_size": 125761, "dataset_size": 1404572}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:47:12+00:00
|
281d45c8cbeb8b88c476ac40c2f4bd1292a20e13
|
# Dataset Card for "mmlu-management-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-management-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:52:19+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 5611, "num_examples": 5}, {"name": "test", "num_bytes": 570225, "num_examples": 103}], "download_size": 101224, "dataset_size": 575836}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:47:43+00:00
|
fef1b1dfb2dc045750bca12a30b78b262896e70c
|
# Dataset Card for "mmlu-marketing-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-marketing-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:52:27+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 7696, "num_examples": 5}, {"name": "test", "num_bytes": 2054321, "num_examples": 234}], "download_size": 228356, "dataset_size": 2062017}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:48:11+00:00
|
354081fd097d6d3c267d9e947c2a0e15cfe807a3
|
# Dataset Card for "mmlu-medical_genetics-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-medical_genetics-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:52:35+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 5908, "num_examples": 5}, {"name": "test", "num_bytes": 655442, "num_examples": 100}], "download_size": 113868, "dataset_size": 661350}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:48:40+00:00
|
a4d7546121719736c84897259480fa5023854f3d
|
# Dataset Card for "mmlu-miscellaneous-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-miscellaneous-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:52:43+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 4890, "num_examples": 5}, {"name": "test", "num_bytes": 3569776, "num_examples": 783}], "download_size": 445448, "dataset_size": 3574666}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:49:10+00:00
|
e18defa3ad5005f7c8a7c8a5ce61fc2861e2004e
|
# Dataset Card for "mmlu-moral_disputes-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-moral_disputes-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:52:52+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 8440, "num_examples": 5}, {"name": "test", "num_bytes": 3543294, "num_examples": 346}], "download_size": 310275, "dataset_size": 3551734}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:49:40+00:00
|
cfd5d9253c7c667616f3e250a94e3bcffab4ea68
|
# Dataset Card for "mmlu-moral_scenarios-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-moral_scenarios-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:53:01+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 11487, "num_examples": 5}, {"name": "test", "num_bytes": 11181249, "num_examples": 895}], "download_size": 574740, "dataset_size": 11192736}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:50:13+00:00
|
2eae87d2aa603f9ace5a46b3535eae1a50a88d12
|
# Dataset Card for "mmlu-nutrition-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-nutrition-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:53:15+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 9632, "num_examples": 5}, {"name": "test", "num_bytes": 3616646, "num_examples": 306}], "download_size": 250211, "dataset_size": 3626278}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:50:44+00:00
|
d25525b53467b998ef0c99797640645a38436fbf
|
# Dataset Card for "mmlu-philosophy-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-philosophy-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:53:25+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 6003, "num_examples": 5}, {"name": "test", "num_bytes": 1928148, "num_examples": 311}], "download_size": 237763, "dataset_size": 1934151}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:51:16+00:00
|
a34b06b67392ca761eab0e687c0bfc9a981b2b14
|
# Dataset Card for "mmlu-prehistory-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-prehistory-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:53:54+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 8827, "num_examples": 5}, {"name": "test", "num_bytes": 3556194, "num_examples": 324}], "download_size": 298181, "dataset_size": 3565021}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:51:49+00:00
|
e233a53f87721deaffa704fff434982c136bd8fc
|
# Dataset Card for "mmlu-professional_accounting-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-professional_accounting-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:54:09+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 10427, "num_examples": 5}, {"name": "test", "num_bytes": 2838796, "num_examples": 282}], "download_size": 349589, "dataset_size": 2849223}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:52:22+00:00
|
cd39189af5e8bfcf08fb5cb62a852ec2dc0dbcdd
|
# Dataset Card for "mmlu-professional_law-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-professional_law-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:54:18+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 24427, "num_examples": 5}, {"name": "test", "num_bytes": 42333466, "num_examples": 1534}], "download_size": 3507499, "dataset_size": 42357893}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:52:58+00:00
|
557d9e025db25227a6deabda7dfdbca26f58a267
|
# Dataset Card for "mmlu-professional_medicine-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-professional_medicine-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:54:34+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 14882, "num_examples": 5}, {"name": "test", "num_bytes": 3843831, "num_examples": 272}], "download_size": 473130, "dataset_size": 3858713}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:53:30+00:00
|
a6b226c2eeef5329e1fee077c13ddbce8040be22
|
# Dataset Card for "mmlu-professional_psychology-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-professional_psychology-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:54:54+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 10024, "num_examples": 5}, {"name": "test", "num_bytes": 7470201, "num_examples": 612}], "download_size": 555481, "dataset_size": 7480225}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:54:05+00:00
|
3e607e836647c476004ade3fe72e6353516cc5f6
|
# Dataset Card for "mmlu-public_relations-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-public_relations-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:55:03+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 7659, "num_examples": 5}, {"name": "test", "num_bytes": 967228, "num_examples": 110}], "download_size": 149601, "dataset_size": 974887}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:54:37+00:00
|
86fe56228b138237d8bbda1bb32f600501b37e0c
|
# Dataset Card for "mmlu-security_studies-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-security_studies-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:55:11+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 19066, "num_examples": 5}, {"name": "test", "num_bytes": 7272697, "num_examples": 245}], "download_size": 419870, "dataset_size": 7291763}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:55:11+00:00
|
125d591554a381d39e3fa6687ab60e5e82a7d3c5
|
# Dataset Card for "mmlu-sociology-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-sociology-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:55:20+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 7680, "num_examples": 5}, {"name": "test", "num_bytes": 1913443, "num_examples": 201}], "download_size": 229587, "dataset_size": 1921123}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:55:44+00:00
|
292d3d36fb80ce1a0c8421474639fb34b72d32f9
|
# Dataset Card for "mmlu-us_foreign_policy-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-us_foreign_policy-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:55:34+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 7808, "num_examples": 5}, {"name": "test", "num_bytes": 939733, "num_examples": 100}], "download_size": 142225, "dataset_size": 947541}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:56:16+00:00
|
995e3005c2970d2ad08a03d370ef360ef9102d46
|
# Dataset Card for "mmlu-virology-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-virology-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:55:43+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 6163, "num_examples": 5}, {"name": "test", "num_bytes": 1105473, "num_examples": 166}], "download_size": 156876, "dataset_size": 1111636}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:56:50+00:00
|
56564cfad5c2d863c1b4652f0563cbe0ddc9380b
|
# Dataset Card for "mmlu-world_religions-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
joey234/mmlu-world_religions-neg-prepend
|
[
"region:us"
] |
2023-04-26T00:55:52+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}, {"name": "negate_openai_prompt", "struct": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "neg_question", "dtype": "string"}, {"name": "fewshot_context", "dtype": "string"}, {"name": "ori_prompt", "dtype": "string"}, {"name": "neg_prompt", "dtype": "string"}, {"name": "fewshot_context_neg", "dtype": "string"}, {"name": "fewshot_context_ori", "dtype": "string"}], "splits": [{"name": "dev", "num_bytes": 4859, "num_examples": 5}, {"name": "test", "num_bytes": 731696, "num_examples": 171}], "download_size": 114166, "dataset_size": 736555}, "configs": [{"config_name": "default", "data_files": [{"split": "dev", "path": "data/dev-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-23T03:57:23+00:00
|
c7e3cbd14b7853efb208da2dcc0776f22aebac1c
|
# Dataset Card for "test-conversation-with-system"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
AlekseyKorshuk/test-conversation-with-system
|
[
"region:us"
] |
2023-04-26T00:58:45+00:00
|
{"dataset_info": {"features": [{"name": "system", "dtype": "string"}, {"name": "conversation", "list": [{"name": "from", "dtype": "string"}, {"name": "role_type", "dtype": "string"}, {"name": "value", "dtype": "string"}]}], "splits": [{"name": "train", "num_bytes": 67027776, "num_examples": 10000}], "download_size": 24743939, "dataset_size": 67027776}}
|
2023-04-26T01:02:51+00:00
|
ec034530c619190ec16af93a87316dc1fe0a5782
|
EdwardLin2023/MELD_Audio_3Labels
|
[
"license:cc-by-4.0",
"region:us"
] |
2023-04-26T01:09:13+00:00
|
{"license": "cc-by-4.0"}
|
2023-04-26T01:10:45+00:00
|
|
11920e97286d3483afe9a12e744e51dde3a011ab
|
# This dataset comes from a Kaggle challenge and can also be found on PSU website.
- https://online.stat.psu.edu/stat508/resource/analysis/gcd
- https://www.kaggle.com/datasets/mpwolke/cusersmarildownloadsgermancsv
---
license: other
language:
- en
tags:
- finance
pretty_name: '-German Credit Risk'
task:
- credit-prediction
size_categories:
- 10K<n<100K
---
## Want to work in a project together or have interest in my services? Reach me:
Linkedin: https://www.linkedin.com/in/marcilioduarte98/
Github: https://github.com/marcilioduarte
@marcilioduarte | Economics and Data Science
|
marcilioduarte/german_credit_risk
|
[
"region:us"
] |
2023-04-26T01:18:22+00:00
|
{}
|
2023-04-26T01:28:40+00:00
|
83d207db6b7316d3e11ef97988d47c5896987e57
|
booknerd/SD
|
[
"license:other",
"region:us"
] |
2023-04-26T01:46:01+00:00
|
{"license": "other"}
|
2023-04-26T01:46:01+00:00
|
|
bf51e94f6c5af35a4e3c70b1d1f6919d7af5dc40
|
# Dataset Card for LAION-art-EN-improved-captions
### Dataset Summary
This dataset has been created by **Re:cast AI** for improving the semantic relationship of image-caption pairs. `generated_captions` were created in a semi-supervised fashion using the **Salesforce/blip2-flan-t5-xxl** model.
### Supported Tasks
Fine-tuning text-to-image generators (e.g. stable-diffusion), or a searchable prompt database (requires faiss-index).
## Dataset Structure
### Data Fields
- orig_caption
- generated_caption
- key
- index
- url
### Data Splits
- train
### Source Data
LAION-Art
|
recastai/LAION-art-EN-improved-captions
|
[
"language:en",
"license:cc-by-4.0",
"region:us"
] |
2023-04-26T02:37:46+00:00
|
{"language": ["en"], "license": "cc-by-4.0", "dataset_info": {"features": [{"name": "orig_caption", "dtype": "string"}, {"name": "generated_caption", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "url", "dtype": "string"}, {"name": "index", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 681710086, "num_examples": 2684160}], "download_size": 441945582, "dataset_size": 681710086}}
|
2023-06-24T03:19:50+00:00
|
82293ed322e798dbe2d1509775bce2a2c40c360b
|
# Dataset Card for "atomic2020-origin"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Estwld/atomic2020-origin
|
[
"region:us"
] |
2023-04-26T03:18:29+00:00
|
{"dataset_info": {"features": [{"name": "knowledge_type", "dtype": "string"}, {"name": "event", "dtype": "string"}, {"name": "relation", "dtype": "string"}, {"name": "relation_description", "dtype": "string"}, {"name": "tail", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 60537042, "num_examples": 300293}, {"name": "validation", "num_bytes": 5678541, "num_examples": 29195}, {"name": "test", "num_bytes": 9184458, "num_examples": 44664}], "download_size": 18270825, "dataset_size": 75400041}}
|
2023-04-26T06:18:11+00:00
|
20ddc161e65b1cd202ab4257a09256fc2575f9a9
|
# Dataset Card for "gpt4all_code"
We provide a code-related subset of the original [nomic-ai/gpt4all-j-prompt-generations](https://huggingface.co/datasets/nomic-ai/gpt4all-j-prompt-generations#dataset-card-for-gpt4all-j-prompt-generations) (v1.2-jazzy revision) dataset, which represents those records whose prompts were sourced from [pacovaldez/stackoverflow-questions](https://huggingface.co/datasets/pacovaldez/stackoverflow-questions) and who explicitly mention one of Python, Java, C++, SQL, Kotlin, PHP, Swift, MATLAB, Typescript, Scala, HTML, CSS, Rust, or Perl. Output records are responses from OpenAI’s GPT3.5-Turbo. Prompt/response pairs have been reformatted to fit the Alpaca format.
Numbers:
- **Prompts**: 93257
- **Tokens**: 87686551 using the [EleutherAI/gpt-neox-20b](https://huggingface.co/EleutherAI/gpt-neox-20b) tokenizer (counting instruction+input+output)
|
lucasmccabe-lmi/gpt4all_code
|
[
"region:us"
] |
2023-04-26T03:25:43+00:00
|
{"dataset_info": {"features": [{"name": "instruction", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 294812377.0, "num_examples": 93257}], "download_size": 143503343, "dataset_size": 294812377.0}}
|
2023-04-26T03:31:11+00:00
|
ca2ff9dde0d732ca656e5ce259018df5acac5c8e
|
# Dataset Card for "codeparrot_apps_alpaca_style"
We provide a subset of [Graverman/Instruct-to-Code](https://huggingface.co/datasets/Graverman/Instruct-to-Code) sourced from [codeparrot/apps](https://huggingface.co/datasets/codeparrot/apps), adjusted to fit into the Alpaca format.
Numbers:
- **Prompts**: 18348
- **Tokens**: 10556319 using the [EleutherAI/gpt-neox-20b](https://huggingface.co/EleutherAI/gpt-neox-20b) tokenizer (counting instruction+input+output)
|
lucasmccabe-lmi/instruct_to_code_alpaca_style
|
[
"region:us"
] |
2023-04-26T03:44:13+00:00
|
{"dataset_info": {"features": [{"name": "instruction", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 31494055.0, "num_examples": 18348}], "download_size": 15597604, "dataset_size": 31494055.0}}
|
2023-04-26T03:47:01+00:00
|
1bc5dfbeb766d03abeddf5a48b9871479a4395bb
|
# Dataset Card for "celeba-hq"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
mattymchen/celeba-hq
|
[
"region:us"
] |
2023-04-26T04:15:42+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "female", "1": "male"}}}}], "splits": [{"name": "train", "num_bytes": 2731627350.0, "num_examples": 28000}, {"name": "validation", "num_bytes": 197550788.0, "num_examples": 2000}], "download_size": 2762109745, "dataset_size": 2929178138.0}}
|
2023-04-26T04:56:53+00:00
|
72196924a4a0fdd3438691707074d5a5ac3e09ee
|
1985prmnt/byznen
|
[
"task_categories:feature-extraction",
"task_categories:conversational",
"task_categories:text-generation",
"task_categories:text2text-generation",
"task_categories:fill-mask",
"size_categories:10K<n<100K",
"license:creativeml-openrail-m",
"doi:10.57967/hf/0575",
"region:us"
] |
2023-04-26T04:32:32+00:00
|
{"license": "creativeml-openrail-m", "size_categories": ["10K<n<100K"], "task_categories": ["feature-extraction", "conversational", "text-generation", "text2text-generation", "fill-mask"], "pretty_name": "ZIGGURAT"}
|
2023-04-26T04:38:57+00:00
|
|
e35e21ac67c5b73485522ffb219989303d008b9f
|
# Dataset Card for "tmp"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
tsungtao/tmp
|
[
"region:us"
] |
2023-04-26T04:38:01+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 1520138.0, "num_examples": 1}], "download_size": 1521322, "dataset_size": 1520138.0}}
|
2023-05-02T12:44:56+00:00
|
3403df578fdf746c8ba5ceac0a6ba5d580532c97
|
新增由@CN_ChiTu训练，底模数据集添加了vctk数据集，修复了变调增强bug的底模，在"fix_pitch_add_vctk_xxxk"目录下,强烈推荐使用这组底模。
新增了"hubertsoft"作为units提取器的底模，在"hubertsoft_fix_pitch_add_vctk_xxxk"目录下，其他的底模都是"contentvec768l12"为units提取器的，两者不通用，在填写config和使用的时候需注意。
将名为"model_0.pt"的预训练模型, 放到config内"expdir: exp/*****"参数指定的模型导出文件夹内, 没有就新建一个, 程序会自动加载该文件夹下的预训练模型.
Move the pre-trained model named "model_0. pt" to the model export folder specified by the "expdir: exp/******" parameter in config, and the program will automatically load the pre-trained models in that folder.
|
ms903/Diff-SVC-refactor-pre-trained-model
|
[
"region:us"
] |
2023-04-26T05:07:49+00:00
|
{}
|
2023-06-21T08:20:53+00:00
|
29ffcabb6f73358aebd66bdcbdd276d71fffdef7
|
zhy123go/hf_test
|
[
"region:us"
] |
2023-04-26T05:50:09+00:00
|
{}
|
2023-08-07T09:48:27+00:00
|
|
8dc922ff7bffed0b155764ed162609db0bf96461
|
# Dataset Card for "cool_new_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
FourthBrainGenAI/MarketMail-AI
|
[
"region:us"
] |
2023-04-26T06:08:24+00:00
|
{"dataset_info": {"features": [{"name": "product", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "marketing_email", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 30474, "num_examples": 17}], "download_size": 31271, "dataset_size": 30474}}
|
2023-04-26T06:08:28+00:00
|
f61ce3d662021ef35caaf435ebbbca9c1560c1ca
|
# Dataset Card for "Food101_test_google_flan_t5_xxl_mode_T_SPECIFIC_A_ns_25250"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/Food101_test_google_flan_t5_xxl_mode_T_SPECIFIC_A_ns_25250
|
[
"region:us"
] |
2023-04-26T06:29:03+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "prompt", "dtype": "string"}, {"name": "true_label", "dtype": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_ViT_L_14_Attributes_ViT_L_14_text_davinci_003_full_clip_tags_ViT_L_14_simple_specific_rices", "num_bytes": 10964582, "num_examples": 25250}, {"name": "fewshot_0_clip_tags_ViT_L_14_Attributes_ViT_L_14_descriptors_text_davinci_003_full_clip_tags_ViT_L_14_simple_specific_rices", "num_bytes": 10964420, "num_examples": 25250}, {"name": "fewshot_0__Attributes_ViT_B_16_descriptors_text_davinci_003_full_clip_tags_ViT_B_16_simple_specific_rices", "num_bytes": 10847652, "num_examples": 25250}, {"name": "fewshot_1__Attributes_ViT_L_14_descriptors_text_davinci_003_full_clip_tags_ViT_L_14_simple_specific_rices", "num_bytes": 21186078, "num_examples": 25250}, {"name": "fewshot_3__Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_clip_tags_LAION_ViT_H_14_2B_simple_specific_rices", "num_bytes": 40504023, "num_examples": 25250}, {"name": "fewshot_1__Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_clip_tags_LAION_ViT_H_14_2B_simple_specific_rices", "num_bytes": 20601481, "num_examples": 25250}, {"name": "fewshot_3__Attributes_ViT_L_14_descriptors_text_davinci_003_full_clip_tags_ViT_L_14_simple_specific_rices", "num_bytes": 41629127, "num_examples": 25250}, {"name": "fewshot_0__Attributes_ViT_L_14_descriptors_text_davinci_003_full_clip_tags_ViT_L_14_simple_specific_rices", "num_bytes": 11496440, "num_examples": 25250}, {"name": "fewshot_0__Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_clip_tags_LAION_ViT_H_14_2B_simple_specific_rices", "num_bytes": 11238021, "num_examples": 25250}], "download_size": 20149636, "dataset_size": 179431824}, "configs": [{"config_name": "default", "data_files": [{"split": "fewshot_0__Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_clip_tags_LAION_ViT_H_14_2B_simple_specific_rices", "path": "data/fewshot_0__Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_clip_tags_LAION_ViT_H_14_2B_simple_specific_rices-*"}]}]}
|
2024-01-30T07:06:18+00:00
|
5d627b31f814d8dbb9bb2c06f744c87234e4b270
|
# Dataset Card for "atomic2020-instruct"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Estwld/atomic2020-instruct
|
[
"region:us"
] |
2023-04-26T06:32:37+00:00
|
{"dataset_info": {"features": [{"name": "knowledge_type", "dtype": "string"}, {"name": "task_type", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 24883204, "num_examples": 58390}, {"name": "test", "num_bytes": 38577951, "num_examples": 89328}, {"name": "train", "num_bytes": 257687540, "num_examples": 600586}], "download_size": 51924047, "dataset_size": 321148695}}
|
2023-05-05T11:35:17+00:00
|
0d4a5da9cd177d21d2b2179962c77a91a398a9ab
|
# Dataset Card for "sample_mnist"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
rassibassi/sample_mnist
|
[
"region:us"
] |
2023-04-26T06:37:01+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "0", "1": "1", "2": "2", "3": "3", "4": "4", "5": "5", "6": "6", "7": "7", "8": "8", "9": "9"}}}}], "splits": [{"name": "train", "num_bytes": 3447853.0, "num_examples": 12000}, {"name": "test", "num_bytes": 563331.0, "num_examples": 2000}], "download_size": 3325934, "dataset_size": 4011184.0}}
|
2023-04-26T06:37:08+00:00
|
9b699742e62719befed15510a5474e1f6c847f2d
|
# Dataset Card for "CNN_small"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CohleM/CNN_small
|
[
"region:us"
] |
2023-04-26T06:46:01+00:00
|
{"dataset_info": {"features": [{"name": "article", "dtype": "string"}, {"name": "highlights", "dtype": "string"}, {"name": "id", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 161497336.8, "num_examples": 40000}, {"name": "test", "num_bytes": 40374334.2, "num_examples": 10000}], "download_size": 128544758, "dataset_size": 201871671.0}}
|
2023-04-26T06:46:48+00:00
|
84af4c2e336790cc2d35db3ca256371fc02f44f4
|
luotr123/sd
|
[
"license:apache-2.0",
"region:us"
] |
2023-04-26T06:48:37+00:00
|
{"license": "apache-2.0"}
|
2023-04-26T06:48:37+00:00
|
|
20e901024969773f529639c36aede78b61c5cf63
|
# Dataset Card for "voxelgym_3c_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Cubpaw/voxelgym_3c_1000
|
[
"region:us"
] |
2023-04-26T06:49:32+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "label", "dtype": "image"}, {"name": "rgb_label", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 1378575.0, "num_examples": 800}, {"name": "validation", "num_bytes": 341336.0, "num_examples": 200}], "download_size": 1035591, "dataset_size": 1719911.0}}
|
2023-04-26T06:50:08+00:00
|
d057aa6dc00d91db0e15109434193139699a26f4
|
## Description
The format of files in each compressed package is as follows:
- 101010001: James trajectory data folder
- 101010002: Curry trajectory data folder
- 101010003: Jokic trajectory data folder
- 101010009: Zion trajectory data folder
- 101010082: Thompson trajectory data folder
- file_index: file index.
#### Explanation of the file index.
- The first-level key represents the corresponding character name. In the example below, 101010001 represents James.
- The second-level key represents the corresponding game session name, where the `c084278fcb164f6db75fe2ebd6f6726e` below corresponds to the second field of the `101010001_c084278fcb164f6db75fe2ebd6f6726e_9_744464.jsonl` file.
- In the third-level key, `summit_level` represents the player's segment corresponding to the trajectory (the higher the level, the higher the player's segment). The number represents the specific round in the game session. In the example below, `0` corresponds to the first round of the game session `c084278fcb164f6db75fe2ebd6f6726e`, which is the third field of the `101010001_c084278fcb164f6db75fe2ebd6f6726e_9_744464.jsonl` file.
- The fourth-level key represents information such as scores, assists, rebounds, and steals in the round.
```
"101010001": {
"c084278fcb164f6db75fe2ebd6f6726e": {
"summit_level": 10,
"0": {
"assist_count": 0,
"block_count": 0,
"blocked_count": 0,
"rebound_count": 0,
"score": 0,
"steal_count": 1,
"stolen_count": 0,
"three_point_count": 0,
"two_point_count": 0
},
"10": {
"assist_count": 0,
"block_count": 0,
"blocked_count": 0,
"rebound_count": 1,
"score": 0,
"steal_count": 0,
"stolen_count": 0,
"three_point_count": 0,
"two_point_count": 0
},
```
|
FUXI/DunkCityDynasty_Dataset
|
[
"region:us"
] |
2023-04-26T06:55:13+00:00
|
{}
|
2023-08-22T04:48:46+00:00
|
5f4adba31dca2e6942340dc8554e25be337eb1c3
|
luotr123/lora
|
[
"license:apache-2.0",
"region:us"
] |
2023-04-26T06:56:10+00:00
|
{"license": "apache-2.0"}
|
2023-04-26T07:49:27+00:00
|
|
f49f467a16f5126e984a53967203e94b82d1bd70
|
# AI Alignment Research Dataset
The AI Alignment Research Dataset is a collection of documents related to AI Alignment and Safety from various books, research papers, and alignment related blog posts. This is a work in progress. Components are still undergoing a cleaning process to be updated more regularly.
## Sources
Here are the list of sources along with sample contents:
- [agentmodel](https://agentmodels.org/)
- [agisf](https://course.aisafetyfundamentals.com/) - recommended readings from AGI Safety Fundamentals
- [aisafety.info](https://aisafety.info/) - Stampy's FAQ
- [alignmentforum](https://www.alignmentforum.org)
- [alignment_newsletter](https://rohinshah.com/alignment-newsletter/)
- [arbital](https://arbital.com/)
- [arxiv](https://arxiv.org/) - relevant research papers
- blogs - entire websites automatically scraped
- [AI Impacts](https://aiimpacts.org/)
- [AI Safety Camp](https://aisafety.camp/)
- [carado.moe](https://carado.moe/)
- [Cold Takes](https://www.cold-takes.com/)
- [DeepMind technical blogs](https://www.deepmind.com/blog-categories/technical-blogs)
- [DeepMind AI Safety Research](https://deepmindsafetyresearch.medium.com/)
- [EleutherAI](https://blog.eleuther.ai/)
- [generative.ink](https://generative.ink/posts/)
- [Gwern Branwen's blog](https://gwern.net/)
- [Jack Clark's Import AI](https://importai.substack.com/)
- [MIRI](https://intelligence.org/)
- [Jacob Steinhardt's blog](https://jsteinhardt.wordpress.com/)
- [ML Safety Newsletter](https://newsletter.mlsafety.org/)
- [Transformer Circuits Thread](https://transformer-circuits.pub/)
- [Open AI Research](https://openai.com/research/)
- [Victoria Krakovna's blog](https://vkrakovna.wordpress.com/)
- [Eliezer Yudkowsky's blog](https://www.yudkowsky.net/)
- [distill](https://distill.pub/)
- [eaforum](https://forum.effectivealtruism.org/) - selected posts
- [lesswrong](https://www.lesswrong.com/) - selected posts
- special_docs - individual documents curated from various resources
- [Make a suggestion](https://bit.ly/ard-suggestion) for sources not already in the dataset
- youtube - playlists & channels
- [AI Alignment playlist](https://www.youtube.com/playlist?list=PLCRVRLd2RhZTpdUdEzJjo3qhmX3y3skWA) and other lists
- [AI Explained](https://www.youtube.com/@aiexplained-official)
- [Evan Hubinger's AI Safety Talks](https://www.youtube.com/@aisafetytalks)
- [AI Safety Reading Group](https://www.youtube.com/@aisafetyreadinggroup/videos)
- [AiTech - TU Delft](https://www.youtube.com/@AiTechTUDelft/)
- [Rob Miles AI](https://www.youtube.com/@RobertMilesAI)
## Keys
All entries contain the following keys:
- `id` - string of unique identifier
- `source` - string of data source listed above
- `title` - string of document title of document
- `authors` - list of strings
- `text` - full text of document content
- `url` - string of valid link to text content
- `date_published` - in UTC format
Additional keys may be available depending on the source document.
## Usage
Execute the following code to download and parse the files:
```python
from datasets import load_dataset
data = load_dataset('StampyAI/alignment-research-dataset')
```
To only get the data for a specific source, pass it in as the second argument, e.g.:
```python
from datasets import load_dataset
data = load_dataset('StampyAI/alignment-research-dataset', 'lesswrong')
```
## Limitations and Bias
LessWrong posts have overweighted content on doom and existential risk, so please beware in training or finetuning generative language models on the dataset.
## Contributing
The scraper to generate this dataset is open-sourced on [GitHub](https://github.com/StampyAI/alignment-research-dataset) and currently maintained by volunteers at StampyAI / AI Safety Info. [Learn more](https://coda.io/d/AI-Safety-Info_dfau7sl2hmG/Get-involved_susRF#_lufSr) or join us on [Discord](https://discord.gg/vjFSCDyMCy).
## Rebuilding info
This README contains info about the number of rows and their features which should be rebuilt each time datasets get changed. To do so, run:
datasets-cli test ./alignment-research-dataset --save_info --all_configs
## Citing the Dataset
For more information, here is the [paper](https://arxiv.org/abs/2206.02841) and [LessWrong](https://www.lesswrong.com/posts/FgjcHiWvADgsocE34/a-descriptive-not-prescriptive-overview-of-current-ai) post. Please use the following citation when using the dataset:
Kirchner, J. H., Smith, L., Thibodeau, J., McDonnell, K., and Reynolds, L. "Understanding AI alignment research: A Systematic Analysis." arXiv preprint arXiv:2022.4338861 (2022).
|
StampyAI/alignment-research-dataset
|
[
"task_categories:question-answering",
"size_categories:10K<n<100K",
"language:en",
"license:mit",
"arxiv:2206.02841",
"region:us"
] |
2023-04-26T07:57:46+00:00
|
{"language": ["en"], "license": "mit", "size_categories": ["10K<n<100K"], "task_categories": ["question-answering"], "pretty_name": "alignment-research-dataset", "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "source", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "text", "dtype": "large_string"}, {"name": "url", "dtype": "string"}, {"name": "date_published", "dtype": "string"}, {"name": "authors", "sequence": "string"}, {"name": "summary", "sequence": "string"}, {"name": "source_type", "dtype": "string"}, {"name": "book_title", "dtype": "string"}, {"name": "karma", "dtype": "int32"}, {"name": "votes", "dtype": "int32"}, {"name": "words", "dtype": "int32"}, {"name": "comment_count", "dtype": "int32"}, {"name": "tags", "sequence": "string"}, {"name": "modified_at", "dtype": "string"}, {"name": "alias", "dtype": "string"}, {"name": "data_last_modified", "dtype": "string"}, {"name": "abstract", "dtype": "string"}, {"name": "author_comment", "dtype": "string"}, {"name": "journal_ref", "dtype": "string"}, {"name": "doi", "dtype": "string"}, {"name": "primary_category", "dtype": "string"}, {"name": "categories", "sequence": "string"}, {"name": "initial_source", "dtype": "string"}, {"name": "bibliography_bib", "sequence": [{"name": "title", "dtype": "string"}]}], "config_name": "all", "splits": [{"name": "train", "num_bytes": 471644446, "num_examples": 14271}], "download_size": 484827959, "dataset_size": 471644446}}
|
2023-11-16T16:58:51+00:00
|
16854f7aee82633beea07dcd990203d00668c6b3
|
phellonchen/video
|
[
"license:cc-by-3.0",
"region:us"
] |
2023-04-26T08:12:45+00:00
|
{"license": "cc-by-3.0"}
|
2023-04-26T08:14:08+00:00
|
|
da15b44c97b12a2d7ab045cbafdaf6f0d69d7e1b
|
xooca/complex_simple_questions
|
[
"license:apache-2.0",
"region:us"
] |
2023-04-26T08:40:26+00:00
|
{"license": "apache-2.0"}
|
2023-04-26T12:53:39+00:00
|
|
21086d86d026022a6c2252c580099f161b25fc1f
|
# Dataset Card for "MarkMail-Dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
FourthBrainGenAI/MarketMail-AI-Dataset
|
[
"region:us"
] |
2023-04-26T08:56:02+00:00
|
{"dataset_info": {"features": [{"name": "product", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "marketing_email", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 10681, "num_examples": 10}], "download_size": 15195, "dataset_size": 10681}}
|
2023-04-26T15:08:12+00:00
|
83f46b69b1a631d7d0a992c566c754d274f3bbe9
|
sample test dataset
|
pythonist/covid
|
[
"license:apache-2.0",
"region:us"
] |
2023-04-26T09:13:44+00:00
|
{"license": "apache-2.0"}
|
2023-04-26T10:19:48+00:00
|
080ab6d095060d134e0b854a68a02a00fea8cb3e
|
AndriiPets/plant-disease-modified
|
[
"license:mit",
"region:us"
] |
2023-04-26T09:28:15+00:00
|
{"license": "mit"}
|
2023-04-26T09:28:15+00:00
|
|
a12db151fd0093e53bfd5946365018dccaeb002c
|
# AutoTrain Dataset for project: car0fil-001
## Dataset Description
This dataset has been automatically processed by AutoTrain for project car0fil-001.
### Languages
The BCP-47 code for the dataset's language is en.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"target": 0,
"text": "And I remember",
"feat_DATE": "2022-09-12T12:29:04",
"feat_PLATFORM": null,
"feat_Unnamed: 4": null,
"feat_Unnamed: 3": null,
"feat_Unnamed: 5": null
},
{
"target": 1,
"text": "Throw a lil \u201cKurt filips is my dad\u201d",
"feat_DATE": "2023-03-27T15:36:21",
"feat_PLATFORM": null,
"feat_Unnamed: 4": null,
"feat_Unnamed: 3": null,
"feat_Unnamed: 5": null
}
]
```
### Dataset Fields
The dataset has the following fields (also called "features"):
```json
{
"target": "ClassLabel(names=['CAROLINE FILIPS', 'NOT CAROLINE'], id=None)",
"text": "Value(dtype='string', id=None)",
"feat_DATE": "Value(dtype='string', id=None)",
"feat_PLATFORM": "Value(dtype='string', id=None)",
"feat_Unnamed: 4": "Value(dtype='float64', id=None)",
"feat_Unnamed: 3": "Value(dtype='float64', id=None)",
"feat_Unnamed: 5": "Value(dtype='float64', id=None)"
}
```
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
| ------------ | ------------------- |
| train | 689784 |
| valid | 172447 |
|
saldigioia/Car0GPT
|
[
"task_categories:text-classification",
"language:en",
"chat",
"persona",
"doi:10.57967/hf/0576",
"region:us"
] |
2023-04-26T09:28:45+00:00
|
{"language": ["en"], "task_categories": ["text-classification"], "pretty_name": "Persona based on Caroline Filips", "tags": ["chat", "persona"]}
|
2023-04-26T09:48:09+00:00
|
9ef677610430f46fb52448cba666f000d918bbec
|
# Dataset Card for "sections"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
justram/sections
|
[
"region:us"
] |
2023-04-26T09:51:53+00:00
|
{"dataset_info": {"features": [{"name": "text_id", "dtype": "string"}, {"name": "page_url", "dtype": "string"}, {"name": "page_title", "dtype": "string"}, {"name": "section_title", "dtype": "string"}, {"name": "context_page_description", "dtype": "string"}, {"name": "context_section_description", "dtype": "string"}, {"name": "media", "sequence": "string"}, {"name": "hierachy", "sequence": "string"}, {"name": "category", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 41979319581, "num_examples": 28473864}], "download_size": 15032145200, "dataset_size": 41979319581}}
|
2023-05-04T16:51:39+00:00
|
e09c24432f69774097a12dbedd38efb43e8b823d
| ERROR: type should be string, got "\n\nhttps://osf.io/dwsnm/" |
j35t3r/robocup-victim-dataset
|
[
"task_categories:image-classification",
"size_categories:1K<n<10K",
"license:mit",
"robotics",
"computer vision",
"region:us"
] |
2023-04-26T09:53:04+00:00
|
{"license": "mit", "size_categories": ["1K<n<10K"], "task_categories": ["image-classification"], "tags": ["robotics", "computer vision"]}
|
2023-04-27T08:20:25+00:00
|
04d4e5ca1dc93606cb58752b0c08331e598743a4
|
Introduction:
The UCF-101 dataset is a widely used benchmark for action recognition in videos. The dataset contains 13,320 videos of 101 action categories, and it was created by collecting YouTube videos and using human annotators to label the action categories. However, the original UCF-101 dataset has certificate issues that may cause difficulties during the download process. Additionally, the dataset is in RAR format, which may not be convenient for some users. Therefore, we have created a ZIP version of the dataset to make it more accessible for researchers and enthusiasts.
Dataset Reproduction:
The dataset was reproduced by downloading the original UCF-101 dataset from the official website (https://www.crcv.ucf.edu/data/UCF101.php) and converting it to ZIP format. The videos were not altered in any way, and the labels and annotations are identical to the original dataset.
Dataset Information:
The UCF-101 dataset consists of 101 action categories, each containing between 24 and 953 videos. The total number of videos is 13,320, and the total size of the dataset is approximately 7.2 GB. The videos have a resolution of 320x240 pixels, and the duration varies between 1 and 30 seconds. The videos were captured from a variety of sources, including YouTube, and they feature people performing different actions, such as playing basketball, riding a bike, or cooking.
Usage:
The UCF-101 dataset can be used for a variety of research projects related to action recognition in videos, such as training and evaluating deep learning models. To use the dataset, simply download the ZIP file from the provided link and extract it to your preferred directory. The dataset is organized by action categories, with each category containing a folder with the corresponding videos. The file names include the action category and the video ID, and the labels are provided in a separate file.
Citation:
If you use this data set, please refer to the following technical report:
Khurram Soomro, Amir Roshan Zamir and Mubarak Shah, UCF101: A Dataset of 101 Human Action Classes From Videos in The Wild., CRCV-TR-12-01, November, 2012.
Contact:
If you have any questions or feedback regarding the UCF-101 dataset reproduction, please contact us at [email protected]
|
quchenyuan/UCF101-ZIP
|
[
"region:us"
] |
2023-04-26T09:55:25+00:00
|
{}
|
2023-04-26T15:58:30+00:00
|
3788b2003aa3458c011e53ffef22e12ee38aea48
|
aravind-selvam/chart_processed_800
|
[
"license:mit",
"region:us"
] |
2023-04-26T09:58:32+00:00
|
{"license": "mit", "dataset_info": {"features": [{"name": "pixel_values", "sequence": {"sequence": {"sequence": "float32"}}}, {"name": "labels", "sequence": "int64"}, {"name": "target_sequence", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 30776344108, "num_examples": 4000}, {"name": "validation", "num_bytes": 7694020630, "num_examples": 1000}], "download_size": 1532163489, "dataset_size": 38470364738}}
|
2023-04-26T10:05:56+00:00
|
|
74d702c990743e8c04d24950f1a34c977579d304
|
gyurcika/beszerzes
|
[
"task_categories:text-classification",
"size_categories:n<1K",
"language:hu",
"license:openrail",
"region:us"
] |
2023-04-26T10:06:42+00:00
|
{"language": ["hu"], "license": "openrail", "size_categories": ["n<1K"], "task_categories": ["text-classification"], "pretty_name": "h"}
|
2023-05-11T10:09:04+00:00
|
|
50cc9bd410c232a9a126591589641b323d6e6f64
|
# VISEM-Tracking-graphs - HuggingFace Repository
This HuggingFace repository contains the pre-generated graphs for the sperm video dataset called VISEM-Tracking (https://huggingface.co/papers/2212.02842) . The graphs represent spatial and temporal relationships between sperm in a video. Spatial edges connect sperms within the same frame, while temporal edges connect sperms across different frames.
The graphs have been generated with varying spatial threshold values: 0.1, 0.2, 0.3, 0.4, and 0.5. Each spatial threshold determines the maximum distance between two nodes for them to be connected in the graph. The repository contains separate directories for each spatial threshold.
The source code used to generate graphs can be found here: https://github.com/vlbthambawita/visem-tracking-graphs
## Repository Structure
The repository is structured as follows:
- `spatial_threshold_0.1`
- `spatial_threshold_0.2`
- `spatial_threshold_0.3`
- `spatial_threshold_0.4`
- `spatial_threshold_0.5`
Inside each `spatial_threshold_X` directory, you will find:
- `frame_graphs`: A directory containing individual frame graphs as GraphML files.
- `video_graph.graphml`: A GraphML file containing the complete video graph.
## Usage
To use the graphs in this repository, you need to:
1. Download the desired graph files (frame graphs or video graph) for the spatial threshold of your choice.
2. Load the graphs using a graph library such as NetworkX in Python:
```python
import networkx as nx
# Load a frame graph
frame_graph = nx.read_graphml('path/to/frame_graph_X.graphml')
# Load the video graph
video_graph = nx.read_graphml('path/to/video_graph.graphml')
```
TO USE THIS DATA, you need to cite the paper:
https://www.nature.com/articles/s41597-023-02173-4
|
SimulaMet-HOST/visem-tracking-graphs
|
[
"license:cc-by-4.0",
"arxiv:2212.02842",
"region:us"
] |
2023-04-26T10:07:48+00:00
|
{"license": "cc-by-4.0"}
|
2023-10-19T06:15:18+00:00
|
55319436ad54b9480cefda6b9d64397de92456dd
|
# Dataset Card for "refcocog"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
jxu124/refcocog
|
[
"region:us"
] |
2023-04-26T11:00:59+00:00
|
{"dataset_info": {"features": [{"name": "image_id", "dtype": "int64"}, {"name": "split", "dtype": "string"}, {"name": "sentences", "list": [{"name": "raw", "dtype": "string"}, {"name": "sent", "dtype": "string"}, {"name": "sent_id", "dtype": "int64"}, {"name": "tokens", "sequence": "string"}]}, {"name": "file_name", "dtype": "string"}, {"name": "category_id", "dtype": "int64"}, {"name": "ann_id", "dtype": "int64"}, {"name": "sent_ids", "sequence": "int64"}, {"name": "ref_id", "dtype": "int64"}, {"name": "raw_anns", "dtype": "string"}, {"name": "raw_image_info", "dtype": "string"}, {"name": "raw_sentences", "dtype": "string"}, {"name": "image_path", "dtype": "string"}, {"name": "bbox", "sequence": "float64"}, {"name": "captions", "sequence": "string"}, {"name": "global_image_id", "dtype": "string"}, {"name": "anns_id", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 10341980, "num_examples": 5023}, {"name": "train", "num_bytes": 87352599, "num_examples": 42226}, {"name": "validation", "num_bytes": 5236723, "num_examples": 2573}], "download_size": 45968855, "dataset_size": 102931302}}
|
2023-05-20T18:00:12+00:00
|
87b2af5927726bed3ee070f03e18fca2a9354109
|
getleft/cat-image-with-imagenet-label
|
[
"license:mit",
"region:us"
] |
2023-04-26T11:34:12+00:00
|
{"license": "mit"}
|
2023-04-26T11:34:12+00:00
|
|
dcb5ffd89b7b03a4c10cfec90b03b6c3d3c73336
|
# Dataset Card for "voxelgym_3c_5000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Cubpaw/voxelgym_3c_5000
|
[
"region:us"
] |
2023-04-26T11:53:19+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "label", "dtype": "image"}, {"name": "rgb_label", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 6810952.0, "num_examples": 4000}, {"name": "validation", "num_bytes": 1713171.0, "num_examples": 1000}], "download_size": 4986999, "dataset_size": 8524123.0}}
|
2023-04-26T11:53:39+00:00
|
61f79cd5ff9debebd4b08bad583c8d3c23311149
|
katebor/taxonomy
|
[
"license:mit",
"region:us"
] |
2023-04-26T12:21:44+00:00
|
{"license": "mit"}
|
2023-08-17T10:16:05+00:00
|
|
7375d86ab8a6ce1117a796112f7e3ca880280b80
|
# Dataset Card for "test_string_to_dict"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
polinaeterna/test_string_to_dict
|
[
"region:us"
] |
2023-04-26T12:44:25+00:00
|
{"dataset_info": {"features": [{"name": "x", "dtype": "int64"}, {"name": "y", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 48, "num_examples": 3}], "download_size": 0, "dataset_size": 48}, "builder_config": {"data_files": [{"split": "train", "pattern": "data/train-*"}]}}
|
2023-04-26T14:55:25+00:00
|
246b339877c679bc89fbd1bf926576558262a009
|
# Dataset Card for "ios_icons"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
akadhim-ai/ios_icons
|
[
"region:us"
] |
2023-04-26T12:57:31+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 768688.0, "num_examples": 10}], "download_size": 769873, "dataset_size": 768688.0}}
|
2023-04-26T12:57:36+00:00
|
86216ea0dd5e6e0c9753b3c5207df3f36d4c91a9
|
# Dataset Card for "MuGeminorum/Pima"
The dataset originates from the National Institute of Diabetes and Digestive and Kidney Diseases and aims to predict the presence or absence of diabetes through diagnostic measurements. The dataset selection adheres to specific constraints imposed on instances drawn from a more extensive database. Notably, all patients represented in this dataset are females aged at least 21, with a Pima Indian heritage.
## Maintenance
```bash
git clone [email protected]:datasets/MuGeminorum/Pima
```
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("MuGeminorum/Pima")
for item in dataset["train"]:
print(item)
for item in dataset["validation"]:
print(item)
for item in dataset["test"]:
print(item)
```
## Mirror
<https://www.modelscope.cn/datasets/MuGeminorum/Pima>
## Reference
[1] [Pima Indians Diabetes Database](https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database)<br>
[2] [Chapter IV ‐ Medical Signal Segmentation and Classification](https://github.com/MuGeminorum/Medical_Image_Computing/wiki/Chapter-IV-%E2%80%90-Medical-Signal-Segmentation-and-Classification)
|
MuGeminorum/Pima
|
[
"task_categories:feature-extraction",
"task_categories:token-classification",
"size_categories:n<1K",
"language:en",
"license:mit",
"biology",
"medical",
"region:us"
] |
2023-04-26T13:10:02+00:00
|
{"language": ["en"], "license": "mit", "size_categories": ["n<1K"], "task_categories": ["feature-extraction", "token-classification"], "pretty_name": "Pima", "tags": ["biology", "medical"]}
|
2024-01-12T16:46:18+00:00
|
9af6caca8491d5ce3506b36de478771b91b8c5f4
|
smellyprepuce/malerecognition
|
[
"license:unlicense",
"region:us"
] |
2023-04-26T13:39:02+00:00
|
{"license": "unlicense"}
|
2023-04-28T21:59:30+00:00
|
|
751fbb8ae3edcc340b29b4d0c6d9074635b6aab4
|
# Dataset Card for "small_conditioned_fill50k"
This dataset contains 1k preprocessed fill50k with my own condition.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
cvtlyp/small_conditioned_fill50k
|
[
"region:us"
] |
2023-04-26T14:40:25+00:00
|
{"dataset_info": {"features": [{"name": "jpg", "dtype": "image"}, {"name": "hint", "dtype": "image"}, {"name": "txt", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 8506150.0, "num_examples": 1000}], "download_size": 7028732, "dataset_size": 8506150.0}}
|
2023-04-26T14:43:41+00:00
|
d7bf5a959013073a38b62a14687070b3a0a3c157
|
# Dataset Card for "mental-risk"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
nlpUc3mStudents/mental-risk-a
|
[
"region:us"
] |
2023-04-26T14:44:29+00:00
|
{"dataset_info": {"features": [{"name": "subject_id", "dtype": "string"}, {"name": "id_message", "dtype": "int64"}, {"name": "date", "dtype": "string"}, {"name": "message", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 800039, "num_examples": 6248}, {"name": "test", "num_bytes": 76071, "num_examples": 624}], "download_size": 475306, "dataset_size": 876110}}
|
2023-05-05T09:06:46+00:00
|
e2c98ecb586a92f6b3248248b5a8749aba3fef93
|
# Dataset Card for "mental-risk-b"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
nlpUc3mStudents/mental-risk-b
|
[
"region:us"
] |
2023-04-26T14:44:36+00:00
|
{"dataset_info": {"features": [{"name": "subject_id", "dtype": "string"}, {"name": "id_message", "dtype": "int64"}, {"name": "date", "dtype": "string"}, {"name": "message", "dtype": "string"}, {"name": "label", "dtype": "float64"}], "splits": [{"name": "train", "num_bytes": 800039, "num_examples": 6248}, {"name": "test", "num_bytes": 76071, "num_examples": 624}], "download_size": 475767, "dataset_size": 876110}}
|
2023-04-26T14:44:45+00:00
|
d20bc7a7facbd5d1ef549b1939abfaf18857d5a9
|
# Dataset Card for "mental-risk-c"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
nlpUc3mStudents/mental-risk-c
|
[
"region:us"
] |
2023-04-26T14:44:45+00:00
|
{"dataset_info": {"features": [{"name": "subject_id", "dtype": "string"}, {"name": "id_message", "dtype": "int64"}, {"name": "date", "dtype": "string"}, {"name": "message", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 800039, "num_examples": 6248}, {"name": "test", "num_bytes": 76071, "num_examples": 624}], "download_size": 475394, "dataset_size": 876110}}
|
2023-04-26T15:34:35+00:00
|
ff4d3d5a2080604de31febccb16e303bd2a91404
|
# Dataset Card for "mental-risk-d"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
nlpUc3mStudents/mental-risk-d
|
[
"region:us"
] |
2023-04-26T14:44:55+00:00
|
{"dataset_info": {"features": [{"name": "subject_id", "dtype": "string"}, {"name": "id_message", "dtype": "int64"}, {"name": "date", "dtype": "string"}, {"name": "message", "dtype": "string"}, {"name": "suffer_in_favour", "dtype": "float64"}, {"name": "suffer_against", "dtype": "float64"}, {"name": "suffer_other", "dtype": "float64"}, {"name": "control", "dtype": "float64"}], "splits": [{"name": "train", "num_bytes": 949991, "num_examples": 6248}, {"name": "test", "num_bytes": 91047, "num_examples": 624}], "download_size": 486498, "dataset_size": 1041038}}
|
2023-04-26T14:45:02+00:00
|
4f47606e4d88ccba2087cf978e08e1b9bd6c0370
|
# MDCT-1k
Over 1000 audio clips from the [Google music captions dataset](https://huggingface.co/datasets/google/MusicCaps) represented as 512x512 time-frequency images. More information is provided in the [report](MP3_diffusion.pdf).
The time-frequency images are created from the MDCT coefficients of the 0-12kHz frequency band for 20 second audio clips.
Other audio diffusion models operate in the space of the magnitude spectrogram or mel magnitude spectrogram. Since the phase is discarded, this requires the use of a vocoder for audio generation. When operating in the space of the mel-spectrogram, high frequencies are represented with insufficient time resolution, leading to a noticable loss of quality.
Operating in the MDCT space does not require a vocoder, nor does it oversample or undersample any range of frequencies.
Please see [this notebook showing how to load the dataset and convert from the MDCT images back to audio](load_dataset.ipynb)
Additionally, [this notebook includes an example of the audio generated by fine tuning on this dataset and shows how to use the inference pipeline](music_inference.ipynb)
|
danjacobellis/MDCT-1k
|
[
"region:us"
] |
2023-04-26T15:09:51+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 378108023.375, "num_examples": 1581}], "download_size": 373552088, "dataset_size": 378108023.375}}
|
2023-08-14T02:07:47+00:00
|
c3eb97da578f1b60e1cc862746104920a4e086a4
|
# Dataset Card for "AToMiC-Texts-v0.2.updated"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
TREC-AToMiC/AToMiC-Texts-v0.2.1
|
[
"region:us"
] |
2023-04-26T15:34:45+00:00
|
{"dataset_info": {"features": [{"name": "text_id", "dtype": "string"}, {"name": "page_url", "dtype": "string"}, {"name": "page_title", "dtype": "string"}, {"name": "section_title", "dtype": "string"}, {"name": "context_page_description", "dtype": "string"}, {"name": "context_section_description", "dtype": "string"}, {"name": "media", "sequence": "string"}, {"name": "hierachy", "sequence": "string"}, {"name": "category", "sequence": "string"}, {"name": "source_id", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 20393084595, "num_examples": 10134744}], "download_size": 7192298025, "dataset_size": 20393084595}}
|
2023-05-04T17:58:43+00:00
|
fafcfc4fee815f7017848e54b26c47ece8ff1626
|
# ITA-CASEHOLD
## Dataset Summary
- This dataset contains the data used in the research of the ITA-CASEHOLD model, an extractive summarization model to extract holdings from Italian Legal Administrative documents.
- The research paper titled 'Legal Holding Extraction from Italian Case Documents using Italian-LEGAL-BERT Text Summarization' is accepted for ICAIL 23.
- It consists of 1101 pairs of judgments and their official holdings between the years 2019 and 2022 from the archives of [Italian Administrative Justice](https://www.giustizia-amministrativa.it/it/web/guest/massime).
- The Administrative Justice system in Italy covers a wide range of issues, including public contracts, environmental protection, public services, immigration, taxes, and compensation for damages caused by the State
### Download the dataset
To download the dataset, use the following lines:
from datasets import load_dataset
dataset = load_dataset("itacasehold/itacasehold")
To split the train, test, and validation dataset, use
dataset = load_dataset("itacasehold/itacasehold", split = 'train')
### Supported Tasks and Leaderboards
Summarization, Multi-class Text classification
### Languages
Italian
### Data Fields
The dataset consists of
- **URL**: link to the document
- **Document**: The document
- **Summary**: The holding of the document
- **Materia** : Legal subject
- **Title** : Title of the document
### Data Splits
- **Train** : 792
- **Validatio** : 88
- **Test** : 221
### Source Data
The data is collected from ['Judicial Administration site'](https://www.giustizia-amministrativa.it/it/web/guest/massime).
### Social Impact of Dataset
Legal holdings are considered the most essential part of a legal decision because they summarize it without going into the merits of the specific case, establish a legal principle and set a legal precedent.
The holdings writing is carried out by legal experts who, starting from a judgment, set out the applied principle of law in a clear, precise, and concise manner.
We approached the problem of extracting legal holdings as an Extractive text summarization task.
This Dataset addresses the Legal holding Extraction topic and so far the first and the only one present in the Italian language.
This dataset contributes to Summarization in the Italian language and Summarization tasks in Legal domains.
Apart from this, the Dataset can also be used as a multi-class text classification task utilizing legal subjects.
### Dataset Limitation
This Dataset specifically focuses on the Italian Legal domain, and it is only in Italian. The documents are only from the period of 2019-2022.
## Additional Information
### Dataset Curators
The Dataset was curated by researchers from Scoula Superiore Sant'Anna as a part of the project ['Guistizia Agile (Agile Justice)'](https://www.unitus.it/it/unitus/mappatura-della-ricerca/articolo/giustizia-agile) funded by the Italian Ministry of Justice.
### Licensing Information
The data sets are distributed under the `Apache 2.0` License. More information about the terms of use of the original data sets is listed [here](https://www.apache.org/licenses/LICENSE-2.0).
### Citation Information
If you use this dataset then, please, cite the following paper:
@inproceedings{10.1145/3594536.3595177,
author = {Licari, Daniele and Bushipaka, Praveen and Marino, Gabriele and Comand\'{e}, Giovanni and Cucinotta, Tommaso},
title = {Legal Holding Extraction from Italian Case Documents using Italian-LEGAL-BERT Text Summarization},
year = {2023},
isbn = {9798400701979},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3594536.3595177},
doi = {10.1145/3594536.3595177},
abstract = {Legal holdings are used in Italy as a critical component of the legal system, serving to establish legal precedents, provide guidance for future legal decisions, and ensure consistency and predictability in the interpretation and application of the law. They are written by domain experts who describe in a clear and concise manner the principle of law applied in the judgments.We introduce a legal holding extraction method based on Italian-LEGAL-BERT to automatically extract legal holdings from Italian cases. In addition, we present ITA-CaseHold, a benchmark dataset for Italian legal summarization. We conducted several experiments using this dataset, as a valuable baseline for future research on this topic.},
booktitle = {Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law},
pages = {148–156},
numpages = {9},
keywords = {Italian-LEGAL-BERT, Holding Extraction, Extractive Text Summarization, Benchmark Dataset},
location = {<conf-loc>, <city>Braga</city>, <country>Portugal</country>, </conf-loc>},
series = {ICAIL '23}
}
|
itacasehold/itacasehold
|
[
"task_categories:summarization",
"task_categories:text-classification",
"size_categories:n<1K",
"language:it",
"license:apache-2.0",
"legal",
"region:us"
] |
2023-04-26T16:05:50+00:00
|
{"language": ["it"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["summarization", "text-classification"], "pretty_name": "ita_casehold", "dataset_info": {"features": [{"name": "url", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "doc", "dtype": "string"}, {"name": "summary", "dtype": "string"}, {"name": "materia", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 25541563, "num_examples": 792}, {"name": "validation", "num_bytes": 2932410, "num_examples": 88}, {"name": "test", "num_bytes": 6870636, "num_examples": 221}], "download_size": 18051772, "dataset_size": 35344609}, "tags": ["legal"]}
|
2024-01-19T13:53:53+00:00
|
fdbd4844636c5677f6bccb793eb3f4d0d6fb7e4f
|
# Dataset Card for "new_meta_format"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
polinaeterna/new_meta_format
|
[
"region:us"
] |
2023-04-26T16:09:22+00:00
|
{"dataset_info": [{"config_name": "custom", "features": [{"name": "x", "dtype": "int64"}, {"name": "y", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 1600, "num_examples": 100}, {"name": "random", "num_bytes": 160, "num_examples": 10}], "download_size": 3650, "dataset_size": 1760}, {"config_name": "default", "features": [{"name": "x", "dtype": "int64"}, {"name": "y", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 1600, "num_examples": 100}, {"name": "random", "num_bytes": 800, "num_examples": 50}], "download_size": 0, "dataset_size": 2400}], "builder_config": [{"config_name": "custom", "data_files": [{"split": "train", "pattern": "custom/train-*"}, {"split": "random", "pattern": "custom/random-*"}]}, {"config_name": "default", "data_files": [{"split": "train", "pattern": "data/train-*"}, {"split": "random", "pattern": "data/random-*"}]}]}
|
2023-04-27T11:44:46+00:00
|
48119c07a34309dce682974bdfe74de19902c123
|
# Dataset Card for "ios_icons_2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
akadhim-ai/ios_icons_2
|
[
"region:us"
] |
2023-04-26T16:35:15+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 768688.0, "num_examples": 10}], "download_size": 769873, "dataset_size": 768688.0}}
|
2023-04-26T16:35:20+00:00
|
3449b87d6fba3b526c0b776705259aff5b58a2fd
|
```
@dataset{poyhonen_teemu_2022_6341173,
author = {Pöyhönen, Teemu and
Hämäläinen, Mika and
Alnajjar, Khalid},
title = {Multilingual Persuasion Dataset},
month = mar,
year = 2022,
publisher = {Zenodo},
doi = {10.5281/zenodo.6341173},
url = {https://doi.org/10.5281/zenodo.6341173}
}
```
|
metaeval/multilingual-persuasion
|
[
"region:us"
] |
2023-04-26T16:45:23+00:00
|
{}
|
2023-04-26T16:48:08+00:00
|
8f21b35f77abb0f9c4b35462079625bec1da24f2
|
# Dataset Card for "reading_comprehension_exercise_dataset_v2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
jmartin233/reading_comprehension_exercise_dataset_v2
|
[
"region:us"
] |
2023-04-26T16:49:34+00:00
|
{"dataset_info": {"features": [{"name": "person", "dtype": "string"}, {"name": "location", "dtype": "string"}, {"name": "grammar", "dtype": "string"}, {"name": "level", "dtype": "string"}, {"name": "passage", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 104862, "num_examples": 171}], "download_size": 53842, "dataset_size": 104862}}
|
2023-04-26T16:49:37+00:00
|
e57c4e88112e045301738d5490d3c99e690cc518
|
sushvij/generativeaisample
|
[
"language:en",
"license:openrail",
"region:us"
] |
2023-04-26T16:52:18+00:00
|
{"language": ["en"], "license": "openrail", "pretty_name": "gai"}
|
2023-04-26T16:56:46+00:00
|
|
a878efe4e8d40bf2d47372aa2454aab50deb2b39
|
webjunkie/housing
|
[
"license:apache-2.0",
"region:us"
] |
2023-04-26T17:02:51+00:00
|
{"license": "apache-2.0"}
|
2023-04-26T17:04:33+00:00
|
|
607e3482c6fbbb1b2e15fadc78ae07bfbd983c3b
|
# Dataset Card for "question_to_sql_with_ddl"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
stjarvie/question_to_sql_with_ddl
|
[
"region:us"
] |
2023-04-26T17:06:56+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "sql", "dtype": "string"}, {"name": "schema", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1856, "num_examples": 10}, {"name": "test", "num_bytes": 2005, "num_examples": 10}], "download_size": 6616, "dataset_size": 3861}}
|
2023-04-26T19:22:59+00:00
|
5c04090639570d1e634fdd9dbe98238cdb8f4a5b
|
# Dataset Card for "datasetTest3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
ambrosemcduffy/blkQA
|
[
"region:us"
] |
2023-04-26T17:17:42+00:00
|
{"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 5956, "num_examples": 62}], "download_size": 3690, "dataset_size": 5956}}
|
2023-04-26T17:17:44+00:00
|
b7441d2251115a454cbee09f7c18b2003ff252a1
|
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed]
|
rrojo/example001
|
[
"language:es",
"region:us"
] |
2023-04-26T17:18:57+00:00
|
{"language": ["es"]}
|
2023-04-26T18:09:21+00:00
|
58f1f5acbfce54561bd0ac09645d740b110027ae
|
# Dataset Card for "hf_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
andrewmclennan/hf_dataset
|
[
"region:us"
] |
2023-04-26T17:21:55+00:00
|
{"dataset_info": {"features": [{"name": "product", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "marketing_email", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 11241, "num_examples": 10}], "download_size": 15049, "dataset_size": 11241}}
|
2023-04-26T17:21:57+00:00
|
12dbd16e92658fa3cb9f2a030ef1e1cf8c25f4a4
|
# Dataset Card for "MarketMail-AI-Dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
LouisSanna/MarketMail-AI-Dataset
|
[
"region:us"
] |
2023-04-26T17:22:25+00:00
|
{"dataset_info": {"features": [{"name": "product", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "marketing_email", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 103701, "num_examples": 100}], "download_size": 63621, "dataset_size": 103701}}
|
2023-04-26T17:58:57+00:00
|
d12eea963d43aedf9821315fd7f4189da1c4b2d6
|
webjunkie/ds
|
[
"license:apache-2.0",
"region:us"
] |
2023-04-26T17:25:10+00:00
|
{"license": "apache-2.0"}
|
2023-04-26T17:25:50+00:00
|
|
553d442b32439138e6d2a12bc1005997b6af7aa5
|
# Dataset Card for "news-article-summary"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
stevendevoe/news-article-summary
|
[
"region:us"
] |
2023-04-26T17:26:14+00:00
|
{"dataset_info": {"features": [{"name": "article", "dtype": "string"}, {"name": "summary", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 296759, "num_examples": 99}], "download_size": 184628, "dataset_size": 296759}}
|
2023-04-26T17:53:09+00:00
|
dd5fbea235e44d896b1fa94570fdc08180a8dad4
|
kayhal/naruda_poems
|
[
"task_categories:text-generation",
"region:us"
] |
2023-04-26T17:28:26+00:00
|
{"task_categories": ["text-generation"]}
|
2023-04-26T17:33:31+00:00
|
|
aca07cc657e0dfe54763ea5c0458c723576f102c
|
# Dataset Card for "wikipedia_random_page_summaries_zh_tw_5k"
`page_title` 是維基百科原始的頁面名稱，因此可能是簡體中文。`page_summary` 則一律是台灣正體版本。
使用了 [vinta/pangu](https://github.com/vinta/pangu.js) 來確保中英文之間都有加上空格。
由 https://github.com/zetavg/LLM-Research/blob/3b79836/Wikipedia_Random_Page_Summaries_Dataset_Generator.ipynb 產生。
|
zetavg/wikipedia_random_page_summaries_zh_tw_5k
|
[
"language:zh",
"region:us"
] |
2023-04-26T17:28:44+00:00
|
{"language": ["zh"], "dataset_info": {"features": [{"name": "page_title", "dtype": "string"}, {"name": "page_summary", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2053192, "num_examples": 4996}], "download_size": 1498828, "dataset_size": 2053192}}
|
2023-04-26T17:40:39+00:00
|
da58f39d156994f5029ab80714c67cb2274cc331
|
# Dataset Card for "workshop_bloom"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
SakisAth/workshop_bloom
|
[
"region:us"
] |
2023-04-26T17:30:35+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 38390, "num_examples": 150}], "download_size": 6482, "dataset_size": 38390}}
|
2023-04-26T17:30:36+00:00
|
24be2b64f28824d60290bfb32553c392608ab99c
|
# Dataset Card for "MarketMail-AI-Dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
dhnanjay/MarketMail-AI-Dataset
|
[
"language:en",
"license:mit",
"region:us"
] |
2023-04-26T17:32:20+00:00
|
{"language": ["en"], "license": "mit", "pretty_name": "MarketingEmails", "dataset_info": {"features": [{"name": "product", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "marketing_email", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 55434, "num_examples": 49}], "download_size": 38882, "dataset_size": 55434}}
|
2023-04-26T18:37:24+00:00
|
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