Instructions to use BenjaminOcampo/model-contrastive-bert__trained-in-ishate__seed-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/model-contrastive-bert__trained-in-ishate__seed-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/model-contrastive-bert__trained-in-ishate__seed-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/model-contrastive-bert__trained-in-ishate__seed-2") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/model-contrastive-bert__trained-in-ishate__seed-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b90c3d10ab21177520d906d6e23c4b5632b752fb32c2e21fdd6148b2e62f80d3
- Size of remote file:
- 440 MB
- SHA256:
- 616996a39ba9c58a1a2f2b30a9aa602f0557f441c4a67135e4576d65db3f9bbd
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