Instructions to use microsoft/deberta-large-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-large-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/deberta-large-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/deberta-large-mnli") model = AutoModelForSequenceClassification.from_pretrained("microsoft/deberta-large-mnli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/deberta-large-mnli: direct link, hf CLI and curl.
- Browser
- Download file 1.62 GB
-
https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/deberta-large-mnli/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/pytorch_model.bin
1.62 GB
- Xet hash:
- 7e40e5d5a25cc3305ebb66126114a7751c8a8e320e45603afbf06d7e5695eb7f
- Size of remote file:
- 1.62 GB
- SHA256:
- 3abd875c9e6dd137a689a1fa1a433f0c2d6bc7462afc42a0095878f88f23be87
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