Instructions to use sm6342/Health101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sm6342/Health101 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sm6342/Health101")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sm6342/Health101") model = AutoModelForMaskedLM.from_pretrained("sm6342/Health101", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from sm6342/Health101: direct link, hf CLI and curl.
- Browser
- Download file 389 MB
-
https://huggingface.co/sm6342/Health101/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://sm6342/Health101@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/sm6342/Health101/resolve/refs%2Fpr%2F1/flax_model.msgpack
389 MB
- Xet hash:
- a2814e56d0af1aedb31e4846ec304b36663f55a6ba024308394cfd4d554abb83
- Size of remote file:
- 389 MB
- SHA256:
- 9275fe9895e7a1461ea4948eb7fce87753f6fb408d3269b519abf77ff59d7694
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