ONE for all, Optimal generator with No Exception.
Project description
MindONE
This repository contains SoTA algorithms, models, and interesting projects in the area of multimodal understanding and content generation
ONE is short for "ONE for all"
News
Hello MindSpore from Stable Diffusion 3!
-
mindone/diffusers now supports Stable Diffusion 3. Give it a try yourself!
import mindspore from mindone.diffusers import StableDiffusion3Pipeline pipe = StableDiffusion3Pipeline.from_pretrained( "stabilityai/stable-diffusion-3-medium-diffusers", mindspore_dtype=mindspore.float16, ) prompt = "A cat holding a sign that says 'Hello MindSpore'" image = pipe(prompt)[0][0] image.save("sd3.png")
supported models under mindone/examples
model | features |
---|---|
hpcai open sora | support v1.0/1.1/1.2 large scale training with dp/sp/zero |
open sora plan | support v1.0/1.1/1.2 large scale training with dp/sp/zero |
stable diffusion | support sd 1.5/2.0/2.1, vanilla fine tune, lora, dreambooth, text inversion |
stable diffusion xl | support sai style(stability AI) vanilla fine tune, lora, dreambooth |
dit | support text to image fine tune |
hunyuan_dit | support text to image fine tune |
pixart_sigma | suuport text to image fine tune at different aspect ratio |
latte | support uncondition text to image fine tune |
animate diff | support motion module and lora training |
dynamicrafter | support image to video generation |
run hf diffusers on mindspore
mindone diffusers is under active development.
component | features |
---|---|
pipeline | support text2image,text2video,text2audio tasks 30+ |
models | support audoencoder & transformers base models same as hf diffusers |
schedulers | support ddpm & dpm solver 10+ schedulers same as hf diffusers |
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