Instructions to use emilyalsentzer/Bio_Discharge_Summary_BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emilyalsentzer/Bio_Discharge_Summary_BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="emilyalsentzer/Bio_Discharge_Summary_BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("emilyalsentzer/Bio_Discharge_Summary_BERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from emilyalsentzer/Bio_Discharge_Summary_BERT: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/emilyalsentzer/Bio_Discharge_Summary_BERT/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://emilyalsentzer/Bio_Discharge_Summary_BERT/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/emilyalsentzer/Bio_Discharge_Summary_BERT/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- a5136f6b4a183eff1aa309be020260126dd1b1bb4fd414696bcdf5a0810d1371
- Size of remote file:
- 433 MB
- SHA256:
- 2f158a0792bc16dcd0d6f9e11f771ec90ac32bb6e77aa185a5d152e01fa8054a
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