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 pytorch_model.bin from hagara/biobert-qa: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/hagara/biobert-qa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hagara/biobert-qa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hagara/biobert-qa/resolve/main/pytorch_model.bin
1.45 GB
- Xet hash:
- def33021fdc39a134b7bc7da9148b28c9b635469ee8a741b04ba4cea34e4e0e7
- Size of remote file:
- 1.45 GB
- SHA256:
- 011f86b0f12b45761a46dc39036570a9f06ded981daae2a024d201960d734cec
路
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