Zero-Shot Classification
Transformers
PyTorch
JAX
bart
text-classification
distilbart
distilbart-mnli
Instructions to use valhalla/distilbart-mnli-12-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use valhalla/distilbart-mnli-12-9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="valhalla/distilbart-mnli-12-9")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("valhalla/distilbart-mnli-12-9") model = AutoModelForSequenceClassification.from_pretrained("valhalla/distilbart-mnli-12-9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from valhalla/distilbart-mnli-12-9: direct link, hf CLI and curl.
- Browser
- Download file 1.43 GB
-
https://huggingface.co/valhalla/distilbart-mnli-12-9/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://valhalla/distilbart-mnli-12-9/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/valhalla/distilbart-mnli-12-9/resolve/main/pytorch_model.bin
1.43 GB
- Xet hash:
- 2d66aece24340059e95a74a9caf098688be996045fe7279d3bc0b1399fc76bfd
- Size of remote file:
- 1.43 GB
- SHA256:
- a6182a9bba1cd3604e0c70b0e8c1a8c4fc6aa9916383f6f9d740fea1780b8608
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