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")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("emilyalsentzer/Bio_ClinicalBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from emilyalsentzer/Bio_ClinicalBERT: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://emilyalsentzer/Bio_ClinicalBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- c128194b3f5912820d2041cb20f347b3025fba5e80396bf54cca2f0f4f92c7d6
- Size of remote file:
- 436 MB
- SHA256:
- a18c4c260fb5c0978b86658615106d5617050b5f14dac6ceb5e0d8beb2f9f719
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