Instructions to use lodestones/MOSS-Image-SFT-8-steps-dmd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lodestones/MOSS-Image-SFT-8-steps-dmd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lodestones/MOSS-Image-SFT-8-steps-dmd", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Could you release a ComfyUI version?
For example: int8_convrot.safetensors
Thanks~
i will if you need me to? i have my environment already setup for the arch
you can just use the lora as is
load it in your lora loader
https://huggingface.co/lodestones/MOSS-Image-SFT-8-steps-dmd/blob/main/lora.safetensors
Thanks, Lora is working now—8 steps.
@lodestones i wonder why the 4 steps can not be loader by a lora loader, and they seem to rely on the time_embedding.safetensors and dataspace.safetensors
how are you guys using it, can anyone share workflow with lora loaded, cause i cant load or work with it all i am getting is smudge, please someone help.
i have a gguf workflow but youll need my nodes
https://huggingface.co/realrebelai/MOSS-Image_GGUFs/tree/main
i have a gguf workflow but youll need my nodes
https://huggingface.co/realrebelai/MOSS-Image_GGUFs/tree/main
can i use your workflow without using gguf models and instead opting for your w4 series
Yes it will work with the w4a8s, I just dont know about bf16 or int8 because my focus is always gguf and w4a8
Yes it will work with the w4a8s, I just dont know about bf16 or int8 because my focus is always gguf and w4a8
can you release moss image w4 version or you have already done, because i know you're fast, also what should i use as edit and nsfw gen model from flux 2 klein 4b, flux3, qwen2.1 , moss, krea2, zimage, idk why but zimage turbo feels better than krea2 as krea doesn't do nsfw much and krea2 models are so big i cant find any smaller than 7 gb , and i am trying my best to avoid ggufs just sticking to int4 int8 w4a4 w6a8 versions thanks.
nodes are updated to run bf16 or int variations now. LoRA support is also active as well.