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: 399 Bytes
47ea602 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"out_dir": "/workspace/runs/main",
"iterations": 2000,
"disc_real": "teacher",
"teacher_dir": "/workspace/teacher",
"p_gan": 0.5,
"micro": 2,
"fake_per_gen": 2,
"fake_warmup": 150,
"adv_start": 50,
"adv_warmup": 200,
"lr_gen": 1.5e-5, "lr_time": 1.5e-5, "lr_q": 1.5e-5,
"ema": 0.998,
"log_every": 10,
"sample_every": 100,
"save_every": 200,
"export_every": 400,
"eval_count": 8
}
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