Upload ONNX weights

#2
by Xenova HF staff - opened
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You can use the following code

from pathlib import Path

from transformers.convert_graph_to_onnx import convert

# Handles all the above steps for you
convert(framework="pt", model="your_path/acge_text_embedding", output=Path("your_path_temp/pytorch_model.onnx"), opset=11)

cite

aspire changed pull request status to closed

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