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ddpm-trucks – AI Model by uzn | AlphaNeural AI
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uzn
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ddpm-trucks
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diffusers
tensorboard
en
uzn/truck
apache-2.0
DDPMPipeline
us
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ddpm-trucks
Model description
This diffusion model is trained with the
🤗 Diffusers
library on the
uzn/truck
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: 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
📈
TensorBoard logs
