v3nu5-cop - SD3.5 Large LoRA Models

Model Description

This repository contains four LoRA (Low-Rank Adaptation) models trained on Stable Diffusion 3.5 Large, designed for generating images with specific styling and characteristics. Each model variant explores different caption preprocessing and optimization approaches.

Model Variants

Model	Caption Type	Optimizer	File
v0b	PREFIX	PRODIGY	sd35L-v3nu5-cop-v0b.safetensors
v0c	PREFIX	ADAMW8BIT	sd35L-v3nu5-cop-v0c.safetensors
v0d	CONTEXT	PRODIGY	sd35L-v3nu5-cop-v0d.safetensors
v0f	CONTEXT	ADAMW8BIT	sd35L-v3nu5-cop-v0f.safetensors

Training Details

• Base Model: Stable Diffusion 3.5 Large
• Training Dataset: mushroomfleet/venus-cop
• Model Type: LoRA (Low-Rank Adaptation)
• Model Size: ~147 MB per variant

Caption Types

• PREFIX: Captions are structured with key descriptors at the beginning
• CONTEXT: Captions provide contextual scene descriptions

Optimizers

• PRODIGY: Advanced adaptive learning rate optimizer
• ADAMW8BIT: Memory-efficient 8-bit AdamW optimizer

Usage

ComfyUI

1. Download the desired .safetensors file
2. Place it in your ComfyUI/models/loras/ directory
3. Load the LoRA in your workflow with appropriate strength (recommended: 0.6-1.0)

Automatic1111/Forge

1. Download the desired .safetensors file
2. Place it in your stable-diffusion-webui/models/Lora/ directory
3. Use in prompts with: <lora:sd35L-v3nu5-cop-v0X:0.8> (replace X with variant)

Diffusers

from diffusers import StableDiffusion3Pipeline
import torch

# Load base model
pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large")

# Load LoRA weights
pipe.load_lora_weights("mushroomfleet/v3nu5-cop", weight_name="sd35L-v3nu5-cop-v0b.safetensors")

# Generate image
prompt = "your prompt here"
image = pipe(prompt, num_inference_steps=28, guidance_scale=4.5).images[0]

Recommended Settings

• Strength: 0.6-1.0
• CFG Scale: 4.5-7.0
• Steps: 28-35
• Sampler: DPM++ 2M or Euler

Model Comparison

Each variant offers different characteristics:

• v0b (PREFIX + PRODIGY): Strong adherence to structured prompting
• v0c (PREFIX + ADAMW8BIT): Balanced approach with prefix structure
• v0d (CONTEXT + PRODIGY): Natural scene understanding
• v0f (CONTEXT + ADAMW8BIT): Contextual generation with efficiency

License

Please refer to the base Stable Diffusion 3.5 Large license terms.

Training Dataset

These models were trained using the venus-cop dataset. Please refer to the dataset page for more information about the training data.

Citation

If you use these models in your work, please consider citing:

@misc{v3nu5-cop-lora,
  title={v3nu5-cop: SD3.5 Large LoRA Models},
  author={mushroomfleet},
  year={2025},
  howpublished={\url{https://huggingface.co/mushroomfleet/v3nu5-cop}}
}

Contact

For questions or issues, please open an issue in this repository or contact through Hugging Face.