Instructions to use CWrecker/Clinical-Longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CWrecker/Clinical-Longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CWrecker/Clinical-Longformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CWrecker/Clinical-Longformer") model = AutoModelForSequenceClassification.from_pretrained("CWrecker/Clinical-Longformer") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b8a20e395d8a5c51176345ae9a6225f4e22c75216f74eebda8b0222cdb0671e
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size 594687412
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