Instructions to use rooftopcoder/bert-base-uncased-coqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rooftopcoder/bert-base-uncased-coqa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="rooftopcoder/bert-base-uncased-coqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("rooftopcoder/bert-base-uncased-coqa") model = AutoModelForQuestionAnswering.from_pretrained("rooftopcoder/bert-base-uncased-coqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rooftopcoder/bert-base-uncased-coqa: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/rooftopcoder/bert-base-uncased-coqa/resolve/028ec1b74d7ed22fd83a51fcba74b89cf26df815/training_args.bin
- Command line
-
hf download hf://rooftopcoder/bert-base-uncased-coqa@028ec1b74d7ed22fd83a51fcba74b89cf26df815/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rooftopcoder/bert-base-uncased-coqa/resolve/028ec1b74d7ed22fd83a51fcba74b89cf26df815/training_args.bin
3.9 kB
- Xet hash:
- d9e907fbc096080dc620282b638fdd700bd8544cd3a2d2153a75c4e1453546d6
- Size of remote file:
- 3.9 kB
- SHA256:
- ccf803d91fe5e14d06c550f007d496384c01d768b58443bc475dea99bf5a8c92
路
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