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
- Xet hash:
- ab0f3283aa540a74927536f4787b387ed94ab5410d7b594a1b3170c6f70b43ed
- Size of remote file:
- 2.99 kB
- SHA256:
- bc383b5651db0bb264bad9740e8b854a6208441cb65120005c8af42af3496518
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