Instructions to use OnePoint16/distilbert-medical-question_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OnePoint16/distilbert-medical-question_answer 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="OnePoint16/distilbert-medical-question_answer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("OnePoint16/distilbert-medical-question_answer") model = AutoModelForQuestionAnswering.from_pretrained("OnePoint16/distilbert-medical-question_answer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.217e858
-
update model card README.md
85d557e -
Model save
bf881f6 -
Training in progress, step 2000
3eefe42 -
Training in progress, step 1500
f18db25 -
Training in progress, step 1000
da2310e -
Training in progress, step 500
24932e4
-
update model card README.md
d476aaf -
Model save
a67ed89 -
initial commit
368360d