Instructions to use emilyalsentzer/Bio_ClinicalBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilyalsentzer/Bio_ClinicalBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="emilyalsentzer/Bio_ClinicalBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("emilyalsentzer/Bio_ClinicalBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from emilyalsentzer/Bio_ClinicalBERT: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://emilyalsentzer/Bio_ClinicalBERT/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- b3edff826f0c3b6dbc30aec97c835d2298d03588d376e59365f014da13e57f25
- Size of remote file:
- 433 MB
- SHA256:
- 23c147c8e9394cd9d9d1849e0b09bc1f75da9a7b4c1a69612e5361a3eef806b4
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