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README.md

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+---
+license: mit
+tags:
+- diffusion
+- anime
+- image-generation
+- pytorch
+---
+
+# Anime Face Diffusion Model
+
+A diffusion model trained to generate 64x64 anime-style faces.
+
+## Model Details
+
+- **Model type**: Denoising Diffusion Probabilistic Model (DDPM)
+- **Training data**: Anime faces dataset
+- **Image size**: 64x64 RGB
+- **Timesteps**: 1000
+- **Architecture**: U-Net with sinusoidal time embeddings
+
+## Usage
+
+```python
+import torch
+from diffusion_model import SimpleUnet, Diffuser  # Your model code
+
+# Load the model
+checkpoint = torch.load("model.pt")
+model = SimpleUnet(in_channels=3)
+model.load_state_dict(checkpoint['ema_model_state_dict'])  # Use EMA weights
+model.eval()
+
+# Generate samples
+# (Add your sampling code here)
+```
+
+## Training Details
+
+- Trained for X epochs
+- Batch size: 64
+- Learning rate: 1e-4
+- EMA decay: 0.9999
+- Noise schedule: Cosine
+
+## Samples
+
+(Add generated sample images here)
+
+## Citation
+
+If you use this model, please cite:
+
+```
+@misc{your-anime-diffusion,
+  author = {Your Name},
+  title = {Anime Face Diffusion Model},
+  year = {2024},
+  publisher = {HuggingFace},
+  url = {https://huggingface.co/your-username/anime-diffusion}
+}
+```

model.pt

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