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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtreviso/roberta-base-snli") model = AutoModelForSequenceClassification.from_pretrained("mtreviso/roberta-base-snli") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
0cc1895 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b6c68b95907c765d5b8a5b51a5f8350760f5082543064d2984bff472d8654108
size 498598977
|