Feature Extraction
Transformers
PyTorch
ONNX
Safetensors
English
bert
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use BAAI/bge-base-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/bge-base-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/bge-base-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-base-en") model = AutoModel.from_pretrained("BAAI/bge-base-en", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding ONNX file of this model (#6)
Verified signature- Adding ONNX file of this model (f7cb5246eef53cdc38b7559fd8ecf840535c9c51) Co-authored-by: Yash <yashvardhan7@users.noreply.huggingface.co>b737bf5
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Merge branch 'main' of https://huggingface.co/BAAI/bge-base-en into main
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Adding `safetensors` variant of this model (#4)
- Adding `safetensors` variant of this model (4a02a27d62d06177efec974767577d23073ffde6) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>90e113f
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