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---
language: en
license: apache-2.0
library_name: diffusers
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
datasets: YaYaB/onepiece-blip-captions
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. -->
# sd-onepiece-diffusers4
## Model description
This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library
on the `YaYaB/onepiece-blip-captions` dataset.
## Intended uses & limitations
#### How to use
```python
# 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: 1
- eval_batch_size: 1
- gradient_accumulation_steps: 4
- optimizer: AdamW with betas=(0.9, 0.999), weight_decay=0.01 and epsilon=1e-08
- lr_scheduler: constant
- lr_warmup_steps: 500
- ema_inv_gamma: None
- ema_inv_gamma: None
- ema_inv_gamma: None
- mixed_precision: fp16
### Training results
📈 [TensorBoard logs](https://huggingface.co/YaYaB/sd-onepiece-diffusers4/tensorboard?#scalars)
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