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runchat/
lora-2ad6897e-00e9-4690-92b5-59875255cacc-o412jz

Name: lora-2ad6897e-00e9-4690-92b5-59875255cacc-o412jz
Availability: InStock

black-forest-labs/FLUX.1-dev

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Flux LoRA: runchat qvm

This is a LoRA (Low-Rank Adaptation) model for Flux.1-dev fine-tuned on images with the trigger word runchat qvm.

Files

pytorch_lora_weights.safetensors: Diffusers format (use with diffusers library)
pytorch_lora_weights_webui.safetensors: Kohya format (use with AUTOMATIC1111, ComfyUI, etc.)

Usage

Diffusers Library

python

from diffusers import FluxPipeline
import torch

# Load base model
pipe = FluxPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-dev",
    torch_dtype=torch.bfloat16
)

# Load LoRA weights (diffusers format)
pipe.load_lora_weights("runchat/lora-2ad6897e-00e9-4690-92b5-59875255cacc-o412jz", weight_name="pytorch_lora_weights.safetensors")
pipe = pipe.to("cuda")

# Generate image
prompt = "a photo of a runchat qvm style"
image = pipe(prompt, num_inference_steps=50, guidance_scale=3.5).images[0]
image.save("output.png")

WebUI (AUTOMATIC1111, ComfyUI, etc.)

Download the pytorch_lora_weights_webui.safetensors file and place it in your WebUI's LoRA directory. Use the trigger word runchat qvm in your prompts.

Training Details

Base model: black-forest-labs/FLUX.1-dev
Training steps: 500
Learning rate: 0.001
Batch size: 2
LoRA rank: 16
Trigger word: runchat qvm

License

This model is trained on Flux.1-dev and inherits its non-commercial license. Please see the license for usage restrictions.