Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ncats/EpiClassify4GARD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncats/EpiClassify4GARD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ncats/EpiClassify4GARD")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ncats/EpiClassify4GARD") model = AutoModelForSequenceClassification.from_pretrained("ncats/EpiClassify4GARD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0ef58038a3c44e44e7671340e6d7af552120fd7f9b51fd3e9982fbc105d01ec
- Size of remote file:
- 433 MB
- SHA256:
- 5a79a4de352e22bdae15bd06619723cc1389321278e4adbd9fb5fc924c8be8b8
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