Instructions to use praneethvasarla/med-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use praneethvasarla/med-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="praneethvasarla/med-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("praneethvasarla/med-bert") model = AutoModelForTokenClassification.from_pretrained("praneethvasarla/med-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from praneethvasarla/med-bert: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/praneethvasarla/med-bert/resolve/main/training_args.bin
- Command line
-
hf download hf://praneethvasarla/med-bert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/praneethvasarla/med-bert/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- f1ef7311a071b9831e2543634e2d3a8a69a01281d564b33a8d8e855cef499092
- Size of remote file:
- 4.54 kB
- SHA256:
- c6e33a9ea11af8a598affa18137cf5c66873406669d63010104b1ee943b61ff1
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