Model Details
Full Model IDBAAI/bge-reranker-large
Pipeline / Taskfeature-extraction
Librarytransformers
Downloads (all-time)775.8K
Likes455
Last Modified5/11/2024
Author / OrgBAAI
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("feature-extraction", model="BAAI/bge-reranker-large")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchonnxsafetensorsxlm-robertatext-classificationmtebfeature-extractionenzharxiv:2401.03462arxiv:2312.15503arxiv:2311.13534arxiv:2310.07554arxiv:2309.07597license:mitmodel-indextext-embeddings-inferenceendpoints_compatibledeploy:azureregion:us
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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: feature-extraction
This model is designed for the feature-extraction task. Explore more models for this use case.
All feature-extraction Models →📊 Popularity
⬇ Downloads775.8K
❤️ Community Likes455
🛠️ 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.