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", 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")Working remote so this is taking longer than I'd like. Uploading four versions. Minimal testing done as I'm away for work. Bob = Made with Bob's upgraded node DMD = DMD lora merged in at 1.0 strength. Saves space and should speed up your generation speed. If you use the non DMD models you will need to load the DMD lora as you normally would at strength 1.0
Check 10Eros discord for sigmas. I used 1.2 sigmas and it was fine however.
10Eros_v1.4_Bob_INT8_Convrot.safetensors
10Eros_v1.4_Bob_DMD_INT8_Convrot.safetensors <- from testing this is the fastest for me on a 3090 and 64GB ram. Most people will want this one.
10Eros_v1.4_int8_convrot.safetensors
10Eros_v1.4_DMD_int8_convrot.safetensors <- this one was expected to be faster but not proving to be. Not sure why. Just testing it for fun.
Resources: https://github.com/BobJohnson24/ComfyUI-INT8-Fast/tree/main
- Downloads last month
- 3,667