moka-ai

/

m3e-base

like 833

https://huggingface.co/moka-ai/m3e-base/blob/main/pytorch_model.bin

huggingface 的项目其实就是一个 git 项目，直接下载就可以了，git clone 这种。

您好，可以说一下具体怎么转吗？这个bin文件不是只有权重
参数吗？

安装 optimum，执行下方代码即可

from optimum.onnxruntime import ORTModelForFeatureExtraction
from transformers import AutoTokenizer

model_checkpoint = "moka-ai/m3e-base"
save_directory = "m3e-base-onnx/"

# Load a model from transformers and export it to ONNX
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
ort_model = ORTModelForFeatureExtraction.from_pretrained(model_checkpoint, export=True, from_transformers=True)

# Save the ONNX model and tokenizer
ort_model.save_pretrained(save_directory)
tokenizer.save_pretrained(save_directory)

具体原理可以参考这个教程 https://huggingface.co/docs/optimum/quicktour#onnx-runtime

安装 optimum，执行下方代码即可

from optimum.onnxruntime import ORTModelForFeatureExtraction
from transformers import AutoTokenizer

model_checkpoint = "moka-ai/m3e-base"
save_directory = "m3e-base-onnx/"

# Load a model from transformers and export it to ONNX
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
ort_model = ORTModelForFeatureExtraction.from_pretrained(model_checkpoint, export=True, from_transformers=True)

# Save the ONNX model and tokenizer
ort_model.save_pretrained(save_directory)
tokenizer.save_pretrained(save_directory)

具体原理可以参考这个教程 https://huggingface.co/docs/optimum/quicktour#onnx-runtime

请问怎么推理呢？