Instructions to use wesleymorris/short-answer-classification-longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wesleymorris/short-answer-classification-longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wesleymorris/short-answer-classification-longformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wesleymorris/short-answer-classification-longformer") model = AutoModelForSequenceClassification.from_pretrained("wesleymorris/short-answer-classification-longformer") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:30db9f91be671e5d0612b85b13117e4d260140a9cdd822d640793f5408b72d36
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size 594678184
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