Model Details
Full Model IDMoritzLaurer/deberta-v3-large-zeroshot-v2.0
Pipeline / Taskzero-shot-classification
Librarytransformers
Downloads (all-time)335.9K
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-zeroshot-v2.0")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformersonnxsafetensorsdeberta-v2text-classificationzero-shot-classificationenarxiv:2312.17543base_model:microsoft/deberta-v3-largebase_model:quantized:microsoft/deberta-v3-largelicense:mitendpoints_compatibleregion:us
More zero-shot-classification Models
See all →🚀 Use This Model
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
⬇ Downloads335.9K
❤️ 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.