Text Classification
sentence-transformers
PyTorch
ONNX
Safetensors
English
Chinese
xlm-roberta
mteb
text-embeddings-inference
Eval Results (legacy)
Instructions to use BAAI/bge-reranker-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/bge-reranker-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/bge-reranker-base") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Inference
- Notebooks
- Google Colab
- Kaggle
Languages covered?
#16
by oliviermills - opened
Where can we find the list of the languages covered. Can we assume performance based on the BGE-m3 languages?
Where can we find the list of the languages covered. Can we assume performance based on the BGE-m3 languages?
Answering my own question found this list here: https://huggingface.co/BAAI/bge-m3/discussions/29#65fab3238e807a4adbfa4f78
Pointing out low-resource languages will perform less well.
oliviermills changed discussion status to closed