Instructions to use darask0/MOSS-Image_4-step_adapter_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use darask0/MOSS-Image_4-step_adapter_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OpenMOSS-Team/MOSS-Image-SFT", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("darask0/MOSS-Image_4-step_adapter_lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download lora.safetensors from darask0/MOSS-Image_4-step_adapter_lora: direct link, hf CLI and curl.
- Browser
- Download file 1.19 GB
-
https://huggingface.co/darask0/MOSS-Image_4-step_adapter_lora/resolve/main/lora.safetensors
- Command line
-
hf download hf://darask0/MOSS-Image_4-step_adapter_lora/lora.safetensors
-
curl -L -o lora.safetensors https://huggingface.co/darask0/MOSS-Image_4-step_adapter_lora/resolve/main/lora.safetensors
1.19 GB
- Xet hash:
- 47780103d9949e61b8834770b3238aa0cfb90151f9eccee073bb1aa61fd6594d
- Size of remote file:
- 1.19 GB
- SHA256:
- 4a4c8e2d6244a0fcdc2822b87b3435226ae57c289aef99fc2ac54edeab9e09bb
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