modelId
stringlengths 4
122
| author
stringlengths 2
42
⌀ | last_modified
timestamp[us, tz=UTC] | downloads
int64 0
74.7M
| likes
int64 0
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| library_name
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84
⌀ | tags
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stringlengths 5
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⌀ | createdAt
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| embedding
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tkcho/commerce-clf-kr-sku-brand-77b272939cef5fe4583e25bc2bc0c00b
|
tkcho
| 2023-11-23T14:50:47Z | 4,463 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T14:50:19Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-1ad4d26590fc6a7153fc3d4dd22fe239
|
tkcho
| 2023-11-24T01:40:01Z | 4,463 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T01:39:29Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-083affdd1c5a9df4b783fdd3f325aaea
|
tkcho
| 2023-11-24T16:21:01Z | 4,463 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T16:20:33Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-253739950719d56fbf5a410812f7aea6
|
tkcho
| 2023-11-24T16:32:49Z | 4,463 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T16:32:19Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-eb57ce6f014e7590ec273483d31cc09c
|
tkcho
| 2023-11-24T17:08:09Z | 4,463 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T17:07:36Z |
Entry not found
|
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] |
oliverguhr/spelling-correction-english-base
|
oliverguhr
| 2023-03-16T18:44:40Z | 4,462 | 41 |
transformers
|
[
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"bart",
"text2text-generation",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] |
text2text-generation
| 2022-05-23T15:26:21Z |
---
language:
- en
license: mit
widget:
- text: "lets do a comparsion"
example_title: "1"
- text: "Their going to be here so0n"
example_title: "2"
- text: "ze shop is cloed due to covid 19"
example_title: "3"
metrics:
- cer
---
This is an experimental model that should fix your typos and punctuation.
If you like to run your own experiments or train for a different language, have a look at [the code](https://github.com/oliverguhr/spelling).
## Model description
This is a proof of concept spelling correction model for English.
## Intended uses & limitations
This project is work in progress, be aware that the model can produce artefacts.
You can test the model using the pipeline-interface:
```python
from transformers import pipeline
fix_spelling = pipeline("text2text-generation",model="oliverguhr/spelling-correction-english-base")
print(fix_spelling("lets do a comparsion",max_length=2048))
```
|
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] |
tkcho/commerce-clf-kr-sku-brand-3328be62d1e5a62e48934c97b62dbd56
|
tkcho
| 2023-11-14T08:54:23Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T13:02:25Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-0054fb04c9135b7b0e74a35d80c8b421
|
tkcho
| 2023-11-28T12:15:33Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T13:58:11Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d1b5373660e55de27fbccfe89a9ea34f
|
tkcho
| 2023-11-16T17:33:52Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T17:33:21Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-4d5a4df4a60aa678e547bf7f34aedf5a
|
tkcho
| 2023-11-17T09:05:06Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T09:04:36Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-b4a4d2b86307d319015a9fe8a0ac33aa
|
tkcho
| 2023-11-17T20:41:01Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T20:40:34Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-bcb5b4f92ae048f63a1108202c136c8d
|
tkcho
| 2023-11-20T07:30:13Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T07:29:38Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-9fffc662f4f339ea78e0060e736f8ada
|
tkcho
| 2023-11-30T03:57:19Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T10:36:44Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-092047f4158e6505b5d2d95dc11e4fd1
|
tkcho
| 2023-11-24T04:14:50Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T04:14:21Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-90c7fd095d7bd220bff7afd5a36fbc7b
|
tkcho
| 2023-11-24T05:02:30Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T05:01:57Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d1c6305184d4a02b8e889bc6514352fb
|
tkcho
| 2023-11-24T18:24:42Z | 4,462 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T18:24:15Z |
Entry not found
|
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] |
emre/whisper-medium-turkish-2
|
emre
| 2023-09-11T12:50:53Z | 4,461 | 3 |
transformers
|
[
"transformers",
"pytorch",
"whisper",
"automatic-speech-recognition",
"tr",
"dataset:mozilla-foundation/common_voice_11_0",
"base_model:openai/whisper-medium",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] |
automatic-speech-recognition
| 2022-12-25T12:35:23Z |
---
language:
- tr
license: apache-2.0
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: Whisper Medium TR - Emre Tasar
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: tr
split: test[:10%]
args: 'config: tr, split: test'
metrics:
- type: wer
value: 18.51
name: Wer
---
# Whisper Medium TR
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.211673
- Wer: 18.51
## Model description
This model is the openai whisper medium transformer adapted for Turkish audio to text transcription. This model has weight decay set to 0.1 to cope with overfitting.
## Intended uses & limitations
The model is available through its [HuggingFace web app](https://huggingface.co/spaces/emre/emre-whisper-medium-turkish-2)
## Training and evaluation data
Data used for training is the initial 10% of train and validation of [Turkish Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/tr/train) 11.0 from Mozilla Foundation.
Weight decay showed to have slightly better result also on the evaluation dataset.
## Training procedure
After loading the pre trained model, it has been trained on the dataset.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
- weight_decay: 0.1
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
|
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] |
tkcho/commerce-clf-kr-brand-domain-b54418483383f45ea8fb6a75dd46034f
|
tkcho
| 2023-11-04T18:31:39Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-04T18:25:06Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-ecd7baa6ebdb967a20df7b6a185f8557
|
tkcho
| 2023-11-15T10:03:02Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-15T10:02:20Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-3fecbdfad5b6427a62c1f15a980f13b2
|
tkcho
| 2023-11-17T14:53:48Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T14:53:19Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-8287c96e2b81d5c8473da70d3db29585
|
tkcho
| 2023-11-17T15:37:24Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T15:36:56Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-227d02fac6697a39192fc7d12289f7c9
|
tkcho
| 2023-11-18T03:07:31Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T03:07:01Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-7c8b8d20a93137d56184b77b26dfb05d
|
tkcho
| 2023-11-29T13:21:49Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T12:58:05Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-551840ccff8b589485e8f4cab276961d
|
tkcho
| 2023-11-20T01:18:57Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T01:18:37Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-54c8c107a3fd5dec2ff279c8286a259e
|
tkcho
| 2023-11-22T06:40:35Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T06:39:56Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-b8c000b060073f6c3e7abbac0b5d0d6e
|
tkcho
| 2023-11-22T10:32:30Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T10:32:00Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-013f48ff647e8dde9da0fac46070c726
|
tkcho
| 2023-11-22T14:20:21Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T14:19:50Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-a641b41f7cc13f52dd6bc3e00e03ae0e
|
tkcho
| 2023-11-22T22:41:16Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T22:40:49Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-2b40769c64833d3556980125ade609b0
|
tkcho
| 2023-11-23T23:56:42Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T23:56:16Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-f5fd4cfa19341c117c373295a4eb3379
|
tkcho
| 2023-11-24T06:43:48Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T06:43:21Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-a846addf5857485d4b94af30d0f5539c
|
tkcho
| 2023-11-24T18:12:58Z | 4,461 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T18:12:30Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-932ec17ba5194ba737c65c87d03d9627
|
tkcho
| 2023-11-26T07:43:19Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T17:18:50Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-267fca937d29fea7c6c5297e2b8fa7bd
|
tkcho
| 2023-11-17T22:07:51Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T22:07:24Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-fdb04277bf5e13ac8fbf3ca45d605472
|
tkcho
| 2023-11-18T17:23:08Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T17:22:35Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-fb3639769ad4bd2915a57e0fa04bb393
|
tkcho
| 2023-11-30T00:05:42Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T13:10:43Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d55b41a14d2cc060329c654c3020ce61
|
tkcho
| 2023-11-21T13:12:34Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T13:12:04Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-51214195137315cf6302eaa3d7e54388
|
tkcho
| 2023-11-21T19:09:39Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T19:09:08Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-662878b8d36d44dad2ad236ea3720315
|
tkcho
| 2023-11-23T04:52:54Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T04:52:15Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-6d996c3e3542574f6b4e29f26267f437
|
tkcho
| 2023-11-23T06:28:57Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T06:28:19Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-4378fb172cd7da8f6cb9f60f69f90e28
|
tkcho
| 2023-11-23T17:08:30Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T17:08:01Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-36bfbb660a18d55f27de85321b4768bf
|
tkcho
| 2023-11-26T02:24:35Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T01:51:22Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-2b4eb431e579820d01343b944a5df8f1
|
tkcho
| 2023-11-24T02:39:48Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T02:39:19Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-67d28eda4472b9e72182c46b9b29765c
|
tkcho
| 2023-11-25T12:00:33Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T05:26:03Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-1ddab1adb73f0a7fb6e27d574e30e426
|
tkcho
| 2023-11-24T06:32:02Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T06:31:15Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-c2b8a8922147185dea18fcef8ee19b3b
|
tkcho
| 2023-11-24T18:01:12Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T18:00:49Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-1386acc2d173c77957b6b1b09778fbcd
|
tkcho
| 2023-11-24T19:53:15Z | 4,460 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T19:52:49Z |
Entry not found
|
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] |
microsoft/wavlm-base-plus-sd
|
microsoft
| 2022-03-25T12:06:46Z | 4,459 | 4 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"audio-frame-classification",
"speech",
"en",
"arxiv:1912.07875",
"arxiv:2106.06909",
"arxiv:2101.00390",
"arxiv:2110.13900",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05Z |
---
language:
- en
tags:
- speech
---
# WavLM-Base-Plus for Speaker Diarization
[Microsoft's WavLM](https://github.com/microsoft/unilm/tree/master/wavlm)
The model was pretrained on 16kHz sampled speech audio with utterance and speaker contrastive loss. When using the model, make sure that your speech input is also sampled at 16kHz.
The model was pre-trained on:
- 60,000 hours of [Libri-Light](https://arxiv.org/abs/1912.07875)
- 10,000 hours of [GigaSpeech](https://arxiv.org/abs/2106.06909)
- 24,000 hours of [VoxPopuli](https://arxiv.org/abs/2101.00390)
[Paper: WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing](https://arxiv.org/abs/2110.13900)
Authors: Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, Jian Wu, Long Zhou, Shuo Ren, Yanmin Qian, Yao Qian, Jian Wu, Michael Zeng, Furu Wei
**Abstract**
*Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing tasks. As speech signal contains multi-faceted information including speaker identity, paralinguistics, spoken content, etc., learning universal representations for all speech tasks is challenging. In this paper, we propose a new pre-trained model, WavLM, to solve full-stack downstream speech tasks. WavLM is built based on the HuBERT framework, with an emphasis on both spoken content modeling and speaker identity preservation. We first equip the Transformer structure with gated relative position bias to improve its capability on recognition tasks. For better speaker discrimination, we propose an utterance mixing training strategy, where additional overlapped utterances are created unsupervisely and incorporated during model training. Lastly, we scale up the training dataset from 60k hours to 94k hours. WavLM Large achieves state-of-the-art performance on the SUPERB benchmark, and brings significant improvements for various speech processing tasks on their representative benchmarks.*
The original model can be found under https://github.com/microsoft/unilm/tree/master/wavlm.
# Fine-tuning details
The model is fine-tuned on the [LibriMix dataset](https://github.com/JorisCos/LibriMix) using just a linear layer for mapping the network outputs.
# Usage
## Speaker Diarization
```python
from transformers import Wav2Vec2FeatureExtractor, WavLMForAudioFrameClassification
from datasets import load_dataset
import torch
dataset = load_dataset("hf-internal-testing/librispeech_asr_demo", "clean", split="validation")
feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained('microsoft/wavlm-base-plus-sd')
model = WavLMForAudioFrameClassification.from_pretrained('microsoft/wavlm-base-plus-sd')
# audio file is decoded on the fly
inputs = feature_extractor(dataset[0]["audio"]["array"], return_tensors="pt")
logits = model(**inputs).logits
probabilities = torch.sigmoid(logits[0])
# labels is a one-hot array of shape (num_frames, num_speakers)
labels = (probabilities > 0.5).long()
```
# License
The official license can be found [here](https://github.com/microsoft/UniSpeech/blob/main/LICENSE)
|
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] |
sgugger/funnel-random-tiny
|
sgugger
| 2021-04-08T19:31:32Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tf",
"funnel",
"feature-extraction",
"endpoints_compatible",
"region:us"
] |
feature-extraction
| 2022-03-02T23:29:05Z |
Entry not found
|
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pankajmathur/model_420
|
pankajmathur
| 2023-11-18T12:13:56Z | 4,459 | 1 |
transformers
|
[
"transformers",
"pytorch",
"llama",
"text-generation",
"en",
"arxiv:2306.02707",
"license:llama2",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-08-03T06:17:15Z |
---
language:
- en
library_name: transformers
license: llama2
---
# model_420
A Llama2-70b model trained on Orca Style datasets.
**P.S. If you're interested to collaborate, please connect with me at www.linkedin.com/in/pankajam**
## Evaluation
We evaluated model_420 on a wide range of tasks using [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) from EleutherAI.
Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|||
|:------:|:--------:|
|**Task**|**Value**|
|*ARC*|0.7014|
|*HellaSwag*|0.8773|
|*MMLU*|0.7035|
|*TruthfulQA*|0.5400|
|*Winogrande*|0.8374|
|*GSM8K*|0.2858|
|*DROP*|0.1435|
|**Total Average**|**0.5841**|
### Prompt Foramt
```
### System:
You are an AI assistant that follows instruction extremely well. Help as much as you can.
### User:
Tell me about Orcas.
### Assistant:
```
#### OobaBooga Instructions:
This model required upto 45GB GPU VRAM in 4bit so it can be loaded directly on Single RTX 6000/L40/A40/A100/H100 GPU or Double RTX 4090/L4/A10/RTX 3090/RTX A5000
So, if you have access to Machine with 45GB GPU VRAM and have installed [OobaBooga Web UI](https://github.com/oobabooga/text-generation-webui) on it.
You can just download this model by using HF repo link directly on OobaBooga Web UI "Model" Tab/Page & Just use **load-in-4bit** option in it.
After that go to Default Tab/Page on OobaBooga Web UI and **copy paste above prompt format into Input** and Enjoy!
<br>
#### Code Instructions:
Below shows a code example on how to use this model
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained("pankajmathur/model_420")
model = AutoModelForCausalLM.from_pretrained(
"pankajmathur/model_420",
torch_dtype=torch.float16,
load_in_4bit=True,
low_cpu_mem_usage=True,
device_map="auto"
)
system_prompt = "### System:\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\n"
#generate text steps
instruction = "Tell me about Orcas."
prompt = f"{system_prompt}### User: {instruction}\n\n### Assistant:\n"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
output = model.generate(**inputs, do_sample=True, top_p=0.95, top_k=0, max_new_tokens=4096)
print(tokenizer.decode(output[0], skip_special_tokens=True))
```
#### Limitations & Biases:
While this model aims for accuracy, it can occasionally produce inaccurate or misleading results.
Despite diligent efforts in refining the pretraining data, there remains a possibility for the generation of inappropriate, biased, or offensive content.
Exercise caution and cross-check information when necessary.
### Citiation:
Please kindly cite using the following BibTeX:
```
@misc{model_51,
author = {Pankaj Mathur},
title = {model_420: An Orca Style Llama2-70b model},
year = {2023},
publisher = {HuggingFace},
journal = {HuggingFace repository},
howpublished = {\url{https://https://huggingface.co/psmathur/model_51},
}
```
```
@misc{mukherjee2023orca,
title={Orca: Progressive Learning from Complex Explanation Traces of GPT-4},
author={Subhabrata Mukherjee and Arindam Mitra and Ganesh Jawahar and Sahaj Agarwal and Hamid Palangi and Ahmed Awadallah},
year={2023},
eprint={2306.02707},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
```
@software{touvron2023llama2,
title={Llama 2: Open Foundation and Fine-Tuned Chat Models},
author={Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava,
Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller,
Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez Madian Khabsa, Isabel Kloumann,
Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov,
Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith,
Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu , Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan,
Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, Thomas Scialom},
year={2023}
}
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_psmathur__model_420)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 58.41 |
| ARC (25-shot) | 70.14 |
| HellaSwag (10-shot) | 87.73 |
| MMLU (5-shot) | 70.35 |
| TruthfulQA (0-shot) | 54.0 |
| Winogrande (5-shot) | 83.74 |
| GSM8K (5-shot) | 28.58 |
| DROP (3-shot) | 14.35 |
|
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] |
tkcho/commerce-clf-kr-brand-domain-ec119aaf02754104de1d0d5045de0789
|
tkcho
| 2023-11-04T18:00:15Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-04T17:53:16Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-5dab338c0ab215375151bc0f09a34fc9
|
tkcho
| 2023-11-14T07:52:01Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T12:39:49Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-2020a857bb7e8b0a15b4dbcb494ffb06
|
tkcho
| 2023-11-15T04:19:06Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-15T04:18:38Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-2e2cf41add5fef0fc4a953c7652c68c7
|
tkcho
| 2023-11-18T13:36:54Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T13:36:27Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-e19dc06f395c94866bf2a838c55dae8c
|
tkcho
| 2023-11-20T05:08:26Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T05:07:50Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-12e0a88fe5192a42a30748c614737a71
|
tkcho
| 2023-11-20T10:39:34Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T10:39:07Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-afcbd2fc936ac99aee180bcd76934808
|
tkcho
| 2023-11-20T22:58:58Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T22:58:27Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-bcdbf8a5d65e350bfc84401932cf76a2
|
tkcho
| 2023-11-22T08:38:27Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T08:37:59Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-1725ce6691ab3b2f88ffadc5661f6389
|
tkcho
| 2023-11-23T05:52:38Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T05:52:09Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-6079a7c4c1cab8e4a06a84acd7c34ff4
|
tkcho
| 2023-11-23T07:52:23Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T07:51:39Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-cd06f340a51e65ecac223d43cd9d3844
|
tkcho
| 2023-11-24T03:51:11Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T03:50:43Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-0317f9a083852d202b151ed730d82f8e
|
tkcho
| 2023-11-24T20:05:00Z | 4,459 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T20:04:32Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-1d008a49af95406c873e831cce4faefd
|
tkcho
| 2023-11-26T07:32:10Z | 4,458 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T16:41:23Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d330a5d311da842d56abf1126dc11d5e
|
tkcho
| 2023-11-27T15:59:33Z | 4,458 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-14T17:52:13Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d6f41b0a212fb43941ebe60437a2eb92
|
tkcho
| 2023-11-26T08:06:21Z | 4,458 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-14T19:27:15Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-7f4c51b36e83382ffc7ece4a64eceb52
|
tkcho
| 2023-11-17T14:32:03Z | 4,458 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T14:31:34Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-f7588925e41352947d85a0df707d4cf0
|
tkcho
| 2023-11-21T14:12:16Z | 4,458 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T14:11:47Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-c9bdfacfc8bdb3617f6af913bc2939e0
|
tkcho
| 2023-11-24T20:11:54Z | 4,458 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T20:10:26Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-acbc727b0f58bfc3e0f836e2a2664a2d
|
tkcho
| 2023-11-27T11:29:11Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T12:04:26Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-7bb094afc38bb0fc4895ea1cf0cf8673
|
tkcho
| 2023-11-12T12:22:19Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T12:21:36Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-208994f0d6b2093beffcab98ea9e1260
|
tkcho
| 2023-11-14T23:07:25Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-14T23:06:57Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-54ff9e9e3a2ec0300d4ce11261f5169f
|
tkcho
| 2023-11-16T03:19:11Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T03:18:36Z |
Entry not found
|
[
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] |
tkcho/commerce-clf-kr-sku-brand-6e5243f32ddb095bb97de057203f7259
|
tkcho
| 2023-11-16T03:50:51Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-16T03:50:24Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-aceb190f35c7a85286a70593bf5ee2cb
|
tkcho
| 2023-11-18T20:36:32Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T20:36:02Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-b93f076ba7e050c010396fbddd051065
|
tkcho
| 2023-11-19T07:13:34Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T07:13:04Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-a8826f76efe3960255a7790ff9b3a2e9
|
tkcho
| 2023-11-19T14:45:35Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-19T14:45:07Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-ea1e1b5d6fa44e0005e559dd564d6cc0
|
tkcho
| 2023-11-20T06:11:02Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T06:10:30Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-9f48070e0e4bc02dd37f2656961971cc
|
tkcho
| 2023-11-22T04:11:01Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T04:10:34Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-50d4204f748c5555fe13b643f4bb1633
|
tkcho
| 2023-11-25T04:07:34Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-22T16:00:12Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-e088ee81006f493629048939878a829c
|
tkcho
| 2023-11-23T03:01:34Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T03:01:00Z |
Entry not found
|
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tkcho/commerce-clf-kr-sku-brand-972b9654badf010d7030a9e112afd8d8
|
tkcho
| 2023-11-23T04:46:52Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T04:46:25Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-fc0de82969affff642900297faccb25a
|
tkcho
| 2023-11-23T08:34:43Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T08:34:00Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-507833992cd9f2081157bfa87bffbdbb
|
tkcho
| 2023-11-23T13:55:49Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T13:55:23Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-1d58e0602ff3b1102ab28b0229aab629
|
tkcho
| 2023-11-23T22:20:58Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T22:20:25Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-e2c65fedc42a4a8073463a073da9c99b
|
tkcho
| 2023-11-24T00:53:29Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T00:53:01Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-4cc10c0ab8aefd62d9a950a2e01ca990
|
tkcho
| 2023-11-24T03:33:25Z | 4,457 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-24T03:32:49Z |
Entry not found
|
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] |
Helsinki-NLP/opus-mt-en-hu
|
Helsinki-NLP
| 2023-08-16T11:29:54Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"en",
"hu",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] |
translation
| 2022-03-02T23:29:04Z |
---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-hu
* source languages: en
* target languages: hu
* OPUS readme: [en-hu](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-hu/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2019-12-18.zip](https://object.pouta.csc.fi/OPUS-MT-models/en-hu/opus-2019-12-18.zip)
* test set translations: [opus-2019-12-18.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-hu/opus-2019-12-18.test.txt)
* test set scores: [opus-2019-12-18.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-hu/opus-2019-12-18.eval.txt)
## Benchmarks
| testset | BLEU | chr-F |
|-----------------------|-------|-------|
| Tatoeba.en.hu | 40.1 | 0.628 |
|
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tkcho/commerce-clf-kr-cate-item-9b9b1e07ab67262226380cf1a9f5c031
|
tkcho
| 2023-11-10T04:05:40Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-10T04:04:59Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-49a9da623283ba8a7a7b5ef306ca93b8
|
tkcho
| 2023-11-12T13:49:39Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T13:47:54Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-d08a788d47dc361acd61cc9f99f9703c
|
tkcho
| 2023-11-26T07:37:42Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-12T16:40:20Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-6ab15a62d61687564e0f89523aa20788
|
tkcho
| 2023-11-17T22:40:05Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-17T22:39:33Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-b742d91d67e2b174ef687e7a7b27250f
|
tkcho
| 2023-11-18T11:58:46Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-18T11:58:14Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-3afcb7f5a638dbadf9fcd498707b121c
|
tkcho
| 2023-11-20T01:32:03Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T01:31:43Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-40e336b1e84b5595895b38a47e7746d8
|
tkcho
| 2023-11-20T07:47:37Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T07:47:06Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-dd25f953787915680aae9f3cd819d3d0
|
tkcho
| 2023-11-25T00:55:17Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T15:07:33Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-70e8913afdf23a6973bfd95976facaf8
|
tkcho
| 2023-11-22T09:34:39Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-20T19:05:05Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-0f6e0c835e01eee8374205c4500a231a
|
tkcho
| 2023-11-21T04:08:19Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T04:07:51Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-2a8f9af2c16a772e546b94bb9fcc30de
|
tkcho
| 2023-11-21T11:31:15Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T11:30:46Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-177491ae6cb73b429e2642db84f9c5a2
|
tkcho
| 2023-11-21T15:59:24Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-21T15:58:51Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-3180bcfc97f76071974376f90d7674cd
|
tkcho
| 2023-11-23T08:04:23Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T08:03:45Z |
Entry not found
|
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] |
tkcho/commerce-clf-kr-sku-brand-90f050cc87ff2e982d1644754ca47f98
|
tkcho
| 2023-11-23T09:16:30Z | 4,456 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-11-23T09:15:58Z |
Entry not found
|
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