Model Details
Full Model IDMoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli
Pipeline / Taskzero-shot-classification
Librarytransformers
Downloads (all-time)72.8K
Likes125
Last Modified4/11/2024
Author / OrgMoritzLaurer
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="MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformerspytorchonnxsafetensorsdeberta-v2text-classificationzero-shot-classificationendataset:multi_nlidataset:facebook/anlidataset:feverdataset:lingnlidataset:alisawuffles/WANLIarxiv:2104.07179arxiv:2111.09543license:mitmodel-indexendpoints_compatibledeploy:azureregion:us
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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.
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⬇ Downloads72.8K
����� Community Likes125
🛠�� 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.