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--- |
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license: cc-by-4.0 |
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datasets: |
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- calm-and-collected/wish_you_were_here |
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language: |
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- en |
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library_name: diffusers |
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pipeline_tag: text-to-image |
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tags: |
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- art |
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- vintage |
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- postcard |
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--- |
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# Wish You Were Here - a 1.5 LORA for vintage postcard replication |
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<!-- Provide a quick summary of what the model is/does. --> |
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Wish you were here is a LORA model developped to create vintage postcard images. The model was trained on Stable Diffusion 1.5. |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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Wish You Were Here (WYWH) is a LORA model developped to replicate the look and feel of vintage postcards. This is done via harvesting public domain images from WikiMedia via |
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manual review and using a combination of manual and automated annotation to describe the images. The specific feature desired to extract were: color, damage and printing |
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technique. The model was developped over a duration of 2 days over 100 epochs of which one epoch was taken as resulting image. |
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- **Developed by:** calm-and-collected |
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- **Model type:** LORA |
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- **License:** CC-BY 4.0 |
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- **Finetuned from model [optional]:** Stable diffusion 1.5 pruned |
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## Bias, Risks, and Limitations |
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The model is trained of images from ~650 images. From observation, the majority of these images are from american origins. The model is thus excelent at replicating USA |
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destinations. The model will also replicate damage seen in the images. |
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[More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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[More Information Needed] |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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## Technical Specifications [optional] |
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#### Hardware |
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The model was trained on two GTX 4090 for a duration of 2 days to extract 100 epochs of the model. |
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#### Software |
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The model was trained via the Kohya_SS gui. |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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## Model Card Contact |
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Use the community section of this repository to contact me. |
