ddpm-butterflies-128
Model description
This diffusion model is trained with the 🤗 Diffusers library
on the huggan/smithsonian_butterflies_subset dataset.
Intended uses & limitations
How to use
from diffusers import DDPMPipeline
model_id = "hjjeon/ddpm-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: 16
- eval_batch_size: 16
- gradient_accumulation_steps: 1
- optimizer: AdamW with betas=(None, None), weight_decay=None and epsilon=None
- lr_scheduler: None
- lr_warmup_steps: 500
- ema_inv_gamma: None
- ema_inv_gamma: None
- ema_inv_gamma: None
- mixed_precision: fp16
Training results
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