Instructions to use simonlevine/clinical-longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonlevine/clinical-longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonlevine/clinical-longformer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonlevine/clinical-longformer") model = AutoModelForMaskedLM.from_pretrained("simonlevine/clinical-longformer", 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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Create README.md
Simon Levinec26dd12
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1000 epoch pre-trained
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500 epochs converted
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initial commit
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