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 training_args.bin from sm6342/Health101: direct link, hf CLI and curl.
- Browser
- Download file 2.35 kB
-
https://huggingface.co/sm6342/Health101/resolve/main/training_args.bin
- Command line
-
hf download hf://sm6342/Health101/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sm6342/Health101/resolve/main/training_args.bin
2.35 kB
- Xet hash:
- daa0ad050a4cd36a82be6809d426e31980150e650ce0413fad9d45b09b02b2fa
- Size of remote file:
- 2.35 kB
- SHA256:
- 984f7e177ac23c4451a5ddfcccc98f6ef83b6113af3e88b12432dbc8144b095d
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