Instructions to use wty500/RL-RIG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wty500/RL-RIG with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wty500/RL-RIG", 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
File size: 276 Bytes
19060f8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"format": "RL-RIG native LoRA tensor names",
"base_model": "Qwen/Qwen-Image-Edit-2511",
"component": "transformer",
"r": 64,
"lora_alpha": 128,
"lora_dropout": 0.0,
"target_modules": [
"to_q",
"to_k",
"to_v",
"to_out.0"
],
"bias": "none"
}
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