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")# 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
- Xet hash:
- a1039377143e409de271d2ad460db5ad3728ee9e515a283e3d01ec11330e3392
- Size of remote file:
- 2.04 GB
- SHA256:
- b48c2b60d9a63b6ad67d99720b4d41ecb235287f10fcaeaae412291cdaf28578
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.