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diffusion_conditional – AI Model by shalpin87 | AlphaNeural AI | AlphaNeural AI
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shalpin87
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diffusion_conditional
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diffusers
en
CelebA
apache-2.0
DDPMConditionalPipeline
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diffusion_conditional
Model description
This diffusion model is trained with the
🤗 Diffusers
library on the
CelebA
dataset.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
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: 1
gradient_accumulation_steps: 1
optimizer: AdamW with betas=(0.95, 0.999), weight_decay=1e-06 and epsilon=1e-08
lr_scheduler: cosine
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
