Instructions to use E-MIMIC/inclusively-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use E-MIMIC/inclusively-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="E-MIMIC/inclusively-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("E-MIMIC/inclusively-classification") model = AutoModelForSequenceClassification.from_pretrained("E-MIMIC/inclusively-classification") - 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 sha256:624a5d71c4eaa9cc92080eeccd567fe05d9796b3ba2d1cf67c5ba017b8113b32
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size 442819684
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