Instructions to use fspanda/Medical-Bio-BERT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fspanda/Medical-Bio-BERT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fspanda/Medical-Bio-BERT2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fspanda/Medical-Bio-BERT2") model = AutoModelForMaskedLM.from_pretrained("fspanda/Medical-Bio-BERT2", 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.4710a97
-
upload flax model
f3fe25c -
allow flax
19b6f22
-
Update vocab.txt
626c118 -
Update pytorch_model.bin
ffa59a7 -
Update config.json
836cfe8 -
Update vocab.txt
97e3fcd -
Update config.json
e6a0f43 -
Update vocab.txt
74be73d -
Update config.json
7f1db9b -
initial commit
28f03ef