Closed iborko closed 2 years ago
Hi @iborko,
import onnx
import onnxconverter_common
new_onnx_model = onnxconverter_common.convert_float_to_float16_model_path("stable-diffusion-v1-4-onnx/unet/1/unet.onnx",keep_io_types=True)
onnx.save(new_onnx_model, 'stable-diffusion-v1-4-onnx/unet/1/unet_fp16.onnx')
Thank you very much!
Hi @iborko
Can you give some details about your hardware and the versions of diffusers and transformers you have been testing to make this Repo running ?
Thanks
I tested this repository on both Amazon G4dn and G5 instances.
You can find exact package versions in my fork: https://github.com/velebit-ai/stable-diffusion-tritonserver
Version from this repo doesn't work anymore because many packages changed their latest versions (including pytorch, diffusers, ...)
Hi! First of all, great repo and very useful. I've been using it with your model export (from huggingface) and everything works great.
But now I have to deploy a different version of Stable Diffusion with Triton server. I saw that you mentioned that you used this script: https://github.com/harishanand95/diffusers/blob/dml/examples/inference/save_onnx.py for model export. That script works for fp32, but how you exported it for fp16? Have you used some kind of converter? Do you have an example of fp16 export?
Thanks :)