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metadata
license: apache-2.0
tags:
  - stable-diffusion
  - text-to-image
  - image-generation
  - realistic-images
  - fine-tuned
datasets:
  - custom-curated-dataset
inference: true
language:
  - en
base_model:
  - stable-diffusion-v1-5/stable-diffusion-v1-5
pipeline_tag: text-to-image
library_name: diffusers

Luna Revamped πŸŒ™

Luna Revamped is a fine-tuned version of Stable Diffusion 1.5, specifically optimized for ultra-realistic image generation of people and environments. Trained on a curated dataset of 100,000 high-quality images, Luna Revamped excels at producing lifelike visuals with remarkable detail and accuracy.


Model Details

  • Base Model: Stable Diffusion 1.5
  • Dataset: Curated collection of 100,000 high-quality images
  • Primary Use: Realistic image generation for people and environments
  • License: Apache 2.0

Model Performance

  • Realism: Delivers stunningly lifelike images.
  • Flexibility: Adapts well to a wide range of text prompts.
  • Fine-Tuned Enhancements: Improved clarity and detail compared to the original Stable Diffusion 1.5.

Usage

Quick Start with Diffusers

from diffusers import StableDiffusionPipeline

# Load the model
model_id = "HyperX-Sentience/luna-revamped"
pipeline = StableDiffusionPipeline.from_pretrained(model_id)
pipeline.to("cuda")

# Generate an image
prompt = "A photorealistic portrait of an astronaut in a futuristic suit"
image = pipeline(prompt).images[0]

# Save the image
image.save("output.png")

Limitations

  • Ethical Use: Ensure the generated images comply with ethical guidelines. Avoid using the model for harmful, deceptive, or malicious purposes.
  • Biases: The model may inherit biases present in the training data. Users should exercise caution and evaluate outputs critically.
  • Edge Cases: In some cases, the model may produce unrealistic or undesired artifacts, especially with ambiguous or complex prompts.