Instructions to use supriyaraj47/roberta-base-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use supriyaraj47/roberta-base-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="supriyaraj47/roberta-base-nli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("supriyaraj47/roberta-base-nli") model = AutoModelForSequenceClassification.from_pretrained("supriyaraj47/roberta-base-nli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from supriyaraj47/roberta-base-nli: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/supriyaraj47/roberta-base-nli/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://supriyaraj47/roberta-base-nli/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/supriyaraj47/roberta-base-nli/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- eec4ff660453c071d32259b353006af3e7f684a66f6e5b5f9cb87019f5707d7a
- Size of remote file:
- 499 MB
- SHA256:
- dc9488b6ec6defc390f1d742a6c36ddcd96af341f40bd131a1f77364fc67fb2e
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