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 training_args.bin from ktrapeznikov/biobert_v1.1_pubmed_squad_v2: direct link, hf CLI and curl.
- Browser
- Download file 1.45 kB
-
https://huggingface.co/ktrapeznikov/biobert_v1.1_pubmed_squad_v2/resolve/main/training_args.bin
- Command line
-
hf download hf://ktrapeznikov/biobert_v1.1_pubmed_squad_v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ktrapeznikov/biobert_v1.1_pubmed_squad_v2/resolve/main/training_args.bin
1.45 kB
- Xet hash:
- f91ee27491672a6927ef524b76bf570f4a83296c3beee27cf50965b3b9c9a337
- Size of remote file:
- 1.45 kB
- SHA256:
- bf9c621ad0233aae43007b1c78c3912b73e9034a9c91a5db32121510ad0e96bc
路
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