
# Disclaimer
This was inspired from https://github.com/YaYaB/finetune-diffusion

# Model Card for Finetuning Stable Diffusion on Vivian Maier's photographs
The main goal is to fine-tune the Stable Diffusion model to generate images reflecting the distinct photographic style of Vivian Maier.

And I chose to utilize a Jupyter Notebook to make the fine-tuning process accessible and easy to understand, particularly for those new to the diffusion pipeline and hugging face API.

# Requirements
To launch the finetuning with a batch_size of 1 you need to have a gpu with at least 24G VRAM (you can use accumulating gradient to simulate higher batch size)

Make sure that you have enough disk space, the model uses ~11Gb

## Examples(at epoch 90)

![vv1.jpg](https://huggingface.co/cQueenccc/Fine-Tune-Diffusion-Vivian/resolve/main/eval/A%20woman%20walking%20down%20the%20street/A%20woman%20walking%20down%20the%20street_90_000000.png)
> A woman walking down a street

![vv2.jpg](https://huggingface.co/cQueenccc/Fine-Tune-Diffusion-Vivian/resolve/main/eval/a%20group%20of%20people%20getting%20on%20a%20bus/a%20group%20of%20people%20getting%20on%20a%20bus_90_000000.png)
> a group of people getting on a bus

![vv3.jpg](https://huggingface.co/cQueenccc/Fine-Tune-Diffusion-Vivian/resolve/main/eval/two%20men%20working%20on%20a%20construction%20site/two%20men%20working%20on%20a%20construction%20site_90_000000.png)
> two man working on a constructing site

## Citation

If you use this dataset, please cite it as:

```
@misc{cqueenccc2023vivian,
      author = {cQueenccc},
      title = {Finetuning Stable Diffusion on Vivian Maier's photographs},
      year={2023},
      howpublished= {\url{https://huggingface.co/cQueenccc/Fine-Tune-Diffusion-Vivian/}}
} 
```
{"language": ["en"], "datasets": ["cQueenccc/Vivian-Blip-Captions"], "pipeline_tag": "text-to-image"}
diffusers tensorboard text-to-image en dataset:cQueenccc/Vivian-Blip-Captions region:us
TAGS
#diffusers #tensorboard #text-to-image #en #dataset-cQueenccc/Vivian-Blip-Captions #region-us 


# Disclaimer
This was inspired from URL

# Model Card for Finetuning Stable Diffusion on Vivian Maier's photographs
The main goal is to fine-tune the Stable Diffusion model to generate images reflecting the distinct photographic style of Vivian Maier.

And I chose to utilize a Jupyter Notebook to make the fine-tuning process accessible and easy to understand, particularly for those new to the diffusion pipeline and hugging face API.

# Requirements
To launch the finetuning with a batch_size of 1 you need to have a gpu with at least 24G VRAM (you can use accumulating gradient to simulate higher batch size)

Make sure that you have enough disk space, the model uses ~11Gb

## Examples(at epoch 90)

!URL
> A woman walking down a street

!URL
> a group of people getting on a bus

!URL
> two man working on a constructing site

If you use this dataset, please cite it as:


# Disclaimer
This was inspired from URL # Model Card for Finetuning Stable Diffusion on Vivian Maier's photographs
The main goal is to fine-tune the Stable Diffusion model to generate images reflecting the distinct photographic style of Vivian Maier.

And I chose to utilize a Jupyter Notebook to make the fine-tuning process accessible and easy to understand, particularly for those new to the diffusion pipeline and hugging face API. # Requirements
To launch the finetuning with a batch_size of 1 you need to have a gpu with at least 24G VRAM (you can use accumulating gradient to simulate higher batch size)

Make sure that you have enough disk space, the model uses ~11Gb ## Examples(at epoch 90)

!URL
> A woman walking down a street

!URL
> a group of people getting on a bus

!URL
> two man working on a constructing site

If you use this dataset, please cite it as:
TAGS
#diffusers #tensorboard #text-to-image #en #dataset-cQueenccc/Vivian-Blip-Captions #region-us 
 # Disclaimer
This was inspired from URL # Model Card for Finetuning Stable Diffusion on Vivian Maier's photographs
The main goal is to fine-tune the Stable Diffusion model to generate images reflecting the distinct photographic style of Vivian Maier.

And I chose to utilize a Jupyter Notebook to make the fine-tuning process accessible and easy to understand, particularly for those new to the diffusion pipeline and hugging face API. # Requirements
To launch the finetuning with a batch_size of 1 you need to have a gpu with at least 24G VRAM (you can use accumulating gradient to simulate higher batch size)

Make sure that you have enough disk space, the model uses ~11Gb ## Examples(at epoch 90)

!URL
> A woman walking down a street

!URL
> a group of people getting on a bus

!URL
> two man working on a constructing site

If you use this dataset, please cite it as:
TAGS
#diffusers #tensorboard #text-to-image #en #dataset-cQueenccc/Vivian-Blip-Captions #region-us 
# Disclaimer
This was inspired from URL# Model Card for Finetuning Stable Diffusion on Vivian Maier's photographs
The main goal is to fine-tune the Stable Diffusion model to generate images reflecting the distinct photographic style of Vivian Maier.

And I chose to utilize a Jupyter Notebook to make the fine-tuning process accessible and easy to understand, particularly for those new to the diffusion pipeline and hugging face API.# Requirements
To launch the finetuning with a batch_size of 1 you need to have a gpu with at least 24G VRAM (you can use accumulating gradient to simulate higher batch size)

Make sure that you have enough disk space, the model uses ~11Gb## Examples(at epoch 90)

!URL
> A woman walking down a street

!URL
> a group of people getting on a bus

!URL
> two man working on a constructing site

If you use this dataset, please cite it as: