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
Commit History
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upload flax model
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allow flax
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First version of the your-model-name model and tokenizer.
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initial commit
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