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mushroomfleet/
v3nu5-cop

Name: v3nu5-cop
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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

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

Automatic1111/Forge

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

Diffusers

python

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:

bibtex

@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.