Create README.md

README.md

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+---
+language: en
+license: apache-2.0
+library_name: diffusers
+tags: []
+datasets: huggan/smithsonian_butterflies_subset
+metrics: []
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# ddpm-ema-flower-64
+
+## Model description
+
+This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library 
+on the `huggan/smithsonian_butterflies_subset` dataset.
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+from diffusers import DDPMPipeline
+
+model_id = "mrm8488/ddpm-ema-butterflies-128"
+
+# load model and scheduler
+pipeline = DDPMPipeline.from_pretrained(model_id)
+
+# run pipeline in inference 
+image = pipeline()["sample"]
+
+# save image
+image[0].save("butterfly.png")
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training data
+
+[TODO: describe the data used to train the model]
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 256
+- eval_batch_size: 128
+- gradient_accumulation_steps: 1
+- optimizer: AdamW with betas=(0.95, 0.999), weight_decay=1e-06 and epsilon=1e-08
+- lr_scheduler: None
+- lr_warmup_steps: 500
+- ema_inv_gamma: 1.0
+- ema_inv_gamma: 0.75
+- ema_inv_gamma: 0.9999
+- mixed_precision: fp16
+
+### Training results
+
+📈 [TensorBoard logs](https://huggingface.co/mrm8488/ddpm-ema-butterflies-128/tensorboard?#scalars)
+