Update README.md

README.md

@@ -7,4 +7,48 @@ library_name: diffusers
 tags:
 - anime
 - generative
----
+---
+
+# anime-faces-ddpm
+A Denoising Diffusion Probabilistic Model (DDPM) trained to generate anime faces using [this example as a basis.](https://github.com/huggingface/diffusers/tree/main/examples/unconditional_image_generation)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65e6420da97628ed6ada1cb8/wM8CUMRQRoOV0FucyRpIi.png)
+
+## Model Description
+
+This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library 
+on the `huggan/anime-faces` dataset.
+
+## How To Use
+
+```python
+from diffusers import DDPMPipeline
+
+checkpoint = "sweetfelinity/anime-faces-ddpm"
+pipeline = DDPMPipeline.from_pretrained(checkpoint)
+pipeline = pipeline.to("cuda") # or "cpu"
+
+for i in range(10):
+    image = pipeline().images[0]
+    image.save(str(i + 1) + ".png")
+```
+
+## Training Hyperparameters
+
+The following hyperparameters were used during training:
+- resolution=64
+- train_batch_size=16
+- num_epochs=30
+- gradient_accumulation_steps=1
+- learning_rate=1e-4
+- lr_warmup_steps=500
+- mixed_precision=fp16
+- checkpointing_steps=2000
+- save_images_epochs=4
+- use_ema
+- adam_weight_decay=1e-6
+- lr_scheduler=linear
+- eval_batch_size=32
+
+## Training Results
+See model folder /generated-images for 100 images created by the DDPM.