Instructions to use CornLogic/10EROS_1.4_Int8_ConvRot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CornLogic/10EROS_1.4_Int8_ConvRot with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CornLogic/10EROS_1.4_Int8_ConvRot", torch_dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
INT4 convrot?
#4
by nosok12313 - opened
Will there be variations using INT4 convrot or mixed INT4 convrot (INT8+INT4)? https://github.com/viralvfx/ComfyUI-INT4-Fast
waiting on this too
Sure I can make these. Wasn't sure of the interest. I'll look into what's best for mixed and post here when I have them done.
Sure I can make these. Wasn't sure of the interest. I'll look into what's best for mixed and post here when I have them done.
there's a good discussion about the different int4 qualities here:
https://www.reddit.com/r/StableDiffusion/s/ZIBiWrq8Qy