Instructions to use mtreviso/roberta-base-snli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtreviso/roberta-base-snli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtreviso/roberta-base-snli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtreviso/roberta-base-snli") model = AutoModelForSequenceClassification.from_pretrained("mtreviso/roberta-base-snli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (3cbcdfe43028654c94c79874db3f21ca99b4b872) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>21a1ee3
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Update README.md
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Duplicate from boychaboy/SNLI_roberta-base
Co-authored-by: Younghoon Jeong <boychaboy@users.noreply.huggingface.co>0cc1895