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
File size: 360 Bytes
47ea602 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"method": "dmad",
"out_dir": "/workspace/runs/dmad",
"teacher_dir": ["/workspace/teacher", "/workspace/teacher2"],
"iterations": 2500,
"micro": 2,
"critic_warmup": 50,
"lr_gen": 2e-5, "lr_time": 2e-5, "lr_q": 2e-5,
"lr_critic": 4e-5,
"ema": 0.998,
"log_every": 10,
"sample_every": 100,
"save_every": 200,
"export_every": 500,
"eval_count": 8
}
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