Feature Extraction
Transformers
PyTorch
ONNX
Safetensors
English
Chinese
xlm-roberta
text-classification
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use BAAI/bge-reranker-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/bge-reranker-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/bge-reranker-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-reranker-large") model = AutoModelForSequenceClassification.from_pretrained("BAAI/bge-reranker-large") - Inference
- Notebooks
- Google Colab
- Kaggle
Add fast tokenizer
#4
by olivierdehaene - opened
No description provided.
olivierdehaene changed pull request status to open
Shitao changed pull request status to merged
Awesome, thanks!