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--- |
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license: apache-2.0 |
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tags: |
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- stable-diffusion |
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- text-to-image |
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- image-generation |
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- realistic-images |
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- fine-tuned |
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datasets: |
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- custom-curated-dataset |
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inference: true |
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language: |
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- en |
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base_model: |
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- stable-diffusion-v1-5/stable-diffusion-v1-5 |
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pipeline_tag: text-to-image |
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library_name: diffusers |
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--- |
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# Luna Revamped 🌙 |
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**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. |
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--- |
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## Model Details |
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- **Base Model**: Stable Diffusion 1.5 |
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- **Dataset**: Curated collection of 100,000 high-quality images |
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- **Primary Use**: Realistic image generation for people and environments |
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- **License**: [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0) |
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--- |
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## Model Performance |
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- **Realism**: Delivers stunningly lifelike images. |
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- **Flexibility**: Adapts well to a wide range of text prompts. |
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- **Fine-Tuned Enhancements**: Improved clarity and detail compared to the original Stable Diffusion 1.5. |
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--- |
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## Usage |
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### Quick Start with Diffusers |
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```python |
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from diffusers import StableDiffusionPipeline |
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# Load the model |
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model_id = "HyperX-Sentience/luna-revamped" |
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pipeline = StableDiffusionPipeline.from_pretrained(model_id) |
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pipeline.to("cuda") |
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# Generate an image |
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prompt = "A photorealistic portrait of an astronaut in a futuristic suit" |
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image = pipeline(prompt).images[0] |
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# Save the image |
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image.save("output.png") |
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``` |
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## Limitations |
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- **Ethical Use**: Ensure the generated images comply with ethical guidelines. Avoid using the model for harmful, deceptive, or malicious purposes. |
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- **Biases**: The model may inherit biases present in the training data. Users should exercise caution and evaluate outputs critically. |
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- **Edge Cases**: In some cases, the model may produce unrealistic or undesired artifacts, especially with ambiguous or complex prompts. |
