Model Details
Full Model IDMoritzLaurer/bge-m3-zeroshot-v2.0
Pipeline / Taskzero-shot-classification
Librarytransformers
Downloads (all-time)62.0K
Likes63
Last Modified4/22/2024
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/bge-m3-zeroshot-v2.0")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformersonnxsafetensorsxlm-robertatext-classificationzero-shot-classificationmultilingualarxiv:2312.17543base_model:BAAI/bge-m3-retromaebase_model:quantized:BAAI/bge-m3-retromaelicense: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
⬇ Downloads62.0K
����� Community Likes63
🛠�� 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.