Instructions to use ktrapeznikov/biobert_v1.1_pubmed_squad_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ktrapeznikov/biobert_v1.1_pubmed_squad_v2 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="ktrapeznikov/biobert_v1.1_pubmed_squad_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ktrapeznikov/biobert_v1.1_pubmed_squad_v2") model = AutoModelForQuestionAnswering.from_pretrained("ktrapeznikov/biobert_v1.1_pubmed_squad_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from ktrapeznikov/biobert_v1.1_pubmed_squad_v2: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/ktrapeznikov/biobert_v1.1_pubmed_squad_v2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://ktrapeznikov/biobert_v1.1_pubmed_squad_v2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/ktrapeznikov/biobert_v1.1_pubmed_squad_v2/resolve/main/flax_model.msgpack
431 MB
- Xet hash:
- 8a49b91f2e455398d30fce0d29b6448cec586d8ea1ed15d00349d4d8d69244f6
- Size of remote file:
- 431 MB
- SHA256:
- 921d8d7d0489b936a4d5a5b76aca83b8646bc4f34e1f9955eb6666a12564f3eb
路
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