Update README.md

README.md

@@ -6,11 +6,110 @@ tags:
 - diffusers
 pipeline_tag: text-to-image
 ---
+
+Here's a draft for your **Skittles v2** model card on Hugging Face:
+
+---
+
+# Skittles v2
+
+## Model Summary
+
+**Skittles v2** is a cutting-edge text-to-image generation model, created by merging components from the **FLUX.1 Schnell** architecture. By combining the precision of **FLUX.1 Schnell** with advanced tweaks, **Skittles v2** is designed to offer high-quality image outputs comparable to **FLUX.1 Dev** while maintaining a streamlined configuration for efficient inference.
+
+- **Type**: Text-to-Image Generation
+- **Architecture**: Merged FLUX.1 Schnell with CFG capabilities
+- **Output Quality**: On par with **FLUX.1 Dev**
+- **Performance**: Optimized for both speed and image fidelity
+
+---
+
+## Features
+
+- **CFG Integration**: Skittles v2 unlocks CFG (Classifier-Free Guidance) capabilities, offering fine-grained control over image generation.
+- **High Fidelity**: Produces ultra-realistic and detailed images.
+- **Optimized Performance**: Merged architecture reduces latency during inference while retaining quality.
+- **Customizable Output**: Supports a wide range of prompts, styles, and configurations.
+
+---
+
+## Model Details
+
+- **Base Model**: FLUX.1 Schnell
+- **Merge Approach**: The model was combined using a custom merging strategy, blending FLUX.1 Schnell’s architecture with optimized CFG decoding.
+- **Training Paradigm**: Not retrained, but restructured for improved inference performance.
+- **Output Size**: Supports resolutions up to 1024x1024 pixels.
+- **Quantization Compatibility**: Works with `optimum-quanto` for FP8 quantization.
+
+---
+
+## Intended Use
+
+### Applications
+- Generating ultra-realistic images for creative projects
+- Creating concept art, visual prototypes, and artistic renderings
+- Exploration of text-to-image synthesis for research or artistic purposes
+
+### Examples
+
+| Prompt | Image Description |
+|-------|--------------------|
+| "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" | Hyper-detailed astronaut surrounded by lush, muted jungle tones |
+| "A futuristic cityscape at sunset, ultra-realistic, cinematic, 4K" | Vibrant, glowing cityscape with dynamic lighting effects |
+| "A delicious ceviche cheesecake slice" | Highly detailed and realistic rendition of a culinary masterpiece |
+
+---
+
+## How to Use
+
 ```python
 from diffusers import DiffusionPipeline
 
+# Load the model
 pipe = DiffusionPipeline.from_pretrained("miike-ai/skittles-v2")
+pipe.to("cuda")  # Ensure CUDA is available
+
+# Generate an image
+prompt = "An ultra-realistic image of a futuristic cityscape."
+image = pipe(prompt, guidance_scale=3.5, num_inference_steps=28).images[0]
+
+# Save the result
+image.save("generated_image.png")
+```
+
+---
+
+## Limitations and Biases
+
+- The model may produce biased or stereotypical outputs based on the provided text prompts.
+- Outputs are deterministic but rely heavily on the prompt quality. Results may vary with ambiguous descriptions.
+- The model is not trained to handle NSFW content or harmful prompts.
+
+---
+
+## Acknowledgments
+
+- Built on top of **FLUX.1 Schnell** by Black Forest Labs
+- Contributions from **miike-ai**
+- Integrated with Hugging Face Diffusers for seamless inference
+
+---
+
+## License
+
+This model is released under the **Apache 2.0 License**.
+
+---
+
+## Citation
+
+If you use **Skittles v2** in your work, please cite:
 
-prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
-image = pipe(prompt).images[0]
-```
+```bibtex
+@misc{miike2024skittlesv2,
+  title={Skittles v2: A Merged Text-to-Image Generation Model},
+  author={miike-ai},
+  year={2024},
+  url={https://huggingface.co/miike-ai/skittles-v2},
+}
+```