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 pytorch_model.bin from sm6342/Health101: direct link, hf CLI and curl.
- Browser
- Download file 389 MB
-
https://huggingface.co/sm6342/Health101/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sm6342/Health101/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sm6342/Health101/resolve/main/pytorch_model.bin
389 MB
- Xet hash:
- 8552846221736bc5408d35b6f652169e7e35da8f973d4d1d43cb4090a4023bd1
- Size of remote file:
- 389 MB
- SHA256:
- c32d8b3f4d65449b35d24fa0443552e85754363f5c57cb995ecf1dc98b52ebea
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