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:
- b75baf673aa92a6fa1c274c1aaa352574fad54272eb35fa1ae045b810711f2fb
- Size of remote file:
- 3.52 kB
- SHA256:
- 6807bc848ff58485d167cd1396a5427cb12f3e7fe3163d0366b16b5319e1ea50
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