nerfmodel

This LoRA captures the distinctive surreal and fantasy visual style of nerfmodel art, showcasing vivid colors and imaginative landscapes. The model excels in generating scenes featuring lone figures in striking environments, such as a barren yellow-orange desert with hints of green vegetation, all while incorporating intricate details like medieval armor and plumes.

Trigger word: nerfmodel

Sample Outputs

Sample 1 Sample 2
This is a digital drawing in a surreal, fantasy style, remin... This is a digital drawing in a surreal, abstract nerfmodel s...
Sample 3 Sample 4
This is a digital drawing in a vibrant, abstract nerfmodel s... This is a digital abstract painting with a dark green backgr...

Usage

ComfyUI

  1. Download the .safetensors file from the Files tab
  2. Place in ComfyUI/models/loras/
  3. Use the Load LoRA node with strength 0.8-1.0
  4. Include nerfmodel in your prompt

Diffusers

import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-dev",
    torch_dtype=torch.bfloat16
)
pipe.load_lora_weights("ms2stationthis/nerfmodel")
pipe.to("cuda")

image = pipe(
    prompt="nerfmodel portrait, soft lighting, detailed",
    guidance_scale=3.5-4.0,
    num_inference_steps=20-30,
    generator=torch.Generator("cuda").manual_seed(42)
).images[0]

image.save("output.png")

Recommended Settings

Parameter Value
LoRA Strength 0.8-1.0
Guidance Scale 3.5-4.0
Inference Steps 20-30
Resolution 1024x1024

Example Prompts

  • nerfmodel this is a digital drawing in a surreal
  • nerfmodel fantasy style
  • nerfmodel yellow-orange desert with sparse green vegetation
  • nerfmodel including a helmet with a red plume

Training Details

  • Base model: black-forest-labs/FLUX.1-dev
  • Training steps: 4000
  • Trigger word: nerfmodel
  • Network: LoRA rank 32, alpha 32
  • Optimizer: adamw8bit, lr 1e-4
  • Precision: float16
  • Resolution: 512, 768, 1024 (multi-res bucketed)

About

Trained using StationThis — an AI creative platform powered by $MS2. Train your own LoRAs via @stationthisbot on Telegram.


Generated by StationThis Training Pipeline

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