Instructions to use BenjaminOcampo/model-bert__trained-in-sbic__seed-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/model-bert__trained-in-sbic__seed-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/model-bert__trained-in-sbic__seed-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/model-bert__trained-in-sbic__seed-3") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/model-bert__trained-in-sbic__seed-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a4d6d2ea3ad58272031058c6ba9aa4879e8429dc24185e87a05b5f2270cbd3b
- Size of remote file:
- 438 MB
- SHA256:
- 65dbd719ef1bb5f1e7426daa502446598c963c8d0c02a469437971e04d1d19dd
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