Instructions to use facebook/bart-large-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/bart-large-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-mnli") model = AutoModelForSequenceClassification.from_pretrained("facebook/bart-large-mnli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download rust_model.ot from facebook/bart-large-mnli: direct link, hf CLI and curl.
- Browser
- Download file 2.04 GB
-
https://huggingface.co/facebook/bart-large-mnli/resolve/refs%2Fpr%2F13/rust_model.ot
- Command line
-
hf download hf://facebook/bart-large-mnli@refs/pr/13/rust_model.ot
-
curl -L -o rust_model.ot https://huggingface.co/facebook/bart-large-mnli/resolve/refs%2Fpr%2F13/rust_model.ot
2.04 GB
- Xet hash:
- a1039377143e409de271d2ad460db5ad3728ee9e515a283e3d01ec11330e3392
- Size of remote file:
- 2.04 GB
- SHA256:
- b48c2b60d9a63b6ad67d99720b4d41ecb235287f10fcaeaae412291cdaf28578
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