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README.md
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license: mit
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This is the ONNX variant of the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) model
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For ONNX export, run:
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onnx_path = Path("bge-base-en-v1.5-dense")
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model.save_pretrained(onnx_path)
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tokenizer.save_pretrained(onnx_path)
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```
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license: mit
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This is the ONNX variant of the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) embeddings model created with the [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) integration.
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For ONNX export, run:
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onnx_path = Path("bge-base-en-v1.5-dense")
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model.save_pretrained(onnx_path)
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tokenizer.save_pretrained(onnx_path)
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```
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Current up-to-date list of sparse and quantized bge ONNX models:
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[zeroshot/bge-large-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-large-en-v1.5-sparse)
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[zeroshot/bge-large-en-v1.5-quant](https://huggingface.co/zeroshot/bge-large-en-v1.5-quant)
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[zeroshot/bge-base-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-base-en-v1.5-sparse)
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[zeroshot/bge-base-en-v1.5-quant](https://huggingface.co/zeroshot/bge-base-en-v1.5-quant)
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[zeroshot/bge-small-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-small-en-v1.5-sparse)
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[zeroshot/bge-small-en-v1.5-quant](https://huggingface.co/zeroshot/bge-small-en-v1.5-quant)
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