Feature Extraction
Transformers
PyTorch
Safetensors
English
bert
mteb
sentence transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use BAAI/bge-small-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/bge-small-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/bge-small-en")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-small-en") model = AutoModel.from_pretrained("BAAI/bge-small-en") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c42ae94c7598447fc4c8961d1cb092c74143149750638e3b4107bb8bcf41c68
- Size of remote file:
- 134 MB
- SHA256:
- 662afbeea6d658f743f3fc11b0e710a0a092837b220eaa7ca0bde604df562153
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