Instructions to use hagara/biobert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hagara/biobert-qa 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="hagara/biobert-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hagara/biobert-qa") model = AutoModelForQuestionAnswering.from_pretrained("hagara/biobert-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hagara/biobert-qa: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/hagara/biobert-qa/resolve/main/training_args.bin
- Command line
-
hf download hf://hagara/biobert-qa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hagara/biobert-qa/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- b2e3b54147e2434b4b79c287ec86b468ee9a66fba963c4135867e784da07748e
- Size of remote file:
- 3.96 kB
- SHA256:
- a870890397dc2f5b9d58fba39b7b03024feed0bf777f3e472879aef83aa3a647
路
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