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")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-base-en") model = AutoModel.from_pretrained("BAAI/bge-base-en") - Inference
- Notebooks
- Google Colab
- Kaggle
Fix library tag
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by osanseviero - opened
README.md
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license: mit
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language:
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---
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```
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## License
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FlagEmbedding is licensed under the [MIT License](https://github.com/FlagOpen/FlagEmbedding/blob/master/LICENSE). The released models can be used for commercial purposes free of charge.
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license: mit
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language:
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library_name: sentence-transformers
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---
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```
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## License
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FlagEmbedding is licensed under the [MIT License](https://github.com/FlagOpen/FlagEmbedding/blob/master/LICENSE). The released models can be used for commercial purposes free of charge.
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