---
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 🌙

**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](https://www.apache.org/licenses/LICENSE-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

```python
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.