How to use the ONNX format of BERT-based model bge-m3, how to load the model and output sentence embeddings.

#52
by panjiayi - opened

How to use the ONNX format of BERT-based model bge-m3, how to load the model and output sentence embeddings. Please tell me. Thank you!

Beijing Academy of Artificial Intelligence org

You can refer to this discussion: https://huggingface.co/BAAI/bge-m3/discussions/50

onnx use cls pooling?
is this right?
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model_ort = ORTModelForFeatureExtraction.from_pretrained(os.path.join(model_path, "onnx"), export=False)

def encode(text):
encoded_input = tokenizer(text, padding=True, truncation=True, return_tensors='pt')
model_output_ort = model_ort(**encoded_input)
return model_output_ort['last_hidden_state'][0][0, :]
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