Instructions to use supriyaraj47/deberta-base-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use supriyaraj47/deberta-base-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="supriyaraj47/deberta-base-nli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("supriyaraj47/deberta-base-nli") model = AutoModelForSequenceClassification.from_pretrained("supriyaraj47/deberta-base-nli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from supriyaraj47/deberta-base-nli: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/supriyaraj47/deberta-base-nli/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://supriyaraj47/deberta-base-nli/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/supriyaraj47/deberta-base-nli/resolve/main/pytorch_model.bin
738 MB
- Xet hash:
- c844ba7af877ff5eec9bfd671f3b88aa7b404c0d5f4d49f08a157deb884d7c08
- Size of remote file:
- 738 MB
- SHA256:
- 9a0e456937106914d5d5d59d0b80a455d4f82880ca0e8be0474f6bd0b6a0ad9b
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