Model Details
Full Model IDjoeddav/xlm-roberta-large-xnli
Pipeline / Taskzero-shot-classification
Librarytransformers
Downloads (all-time)447.1K
Likes302
Last Modified10/16/2024
Author / Orgjoeddav
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("zero-shot-classification", model="joeddav/xlm-roberta-large-xnli")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfsafetensorsxlm-robertatext-classificationtensorflowzero-shot-classificationmultilingualenfresdeelbgrutrarvithzhhiswurdataset:multi_nlidataset:xnliarxiv:1911.02116doi:10.57967/hf/6544license:mitendpoints_compatible
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: zero-shot-classification
This model is designed for the zero-shot-classification task. Explore more models for this use case.
All zero-shot-classification Models →📊 Popularity
⬇ Downloads447.1K
❤️ Community Likes302
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.