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README.md

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 ---
 license: cc-by-4.0
+datasets:
+- calm-and-collected/wish_you_were_here
+language:
+- en
+library_name: diffusers
+pipeline_tag: text-to-image
+tags:
+- art
+- vintage
+- postcard
 ---
+# Wish You Were Here - a 1.5 LORA for vintage postcard replication
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+Wish you were here is a LORA model developped to create vintage postcard images. The model was trained on Stable Diffusion 1.5.
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+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
+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
+technique. The model was developped over a duration of 2 days over 100 epochs of which one epoch was taken as resulting image.
+
+
+- **Developed by:** calm-and-collected
+- **Model type:** LORA
+- **License:** CC-BY 4.0
+- **Finetuned from model [optional]:** Stable diffusion 1.5 pruned
+
+## Bias, Risks, and Limitations
+
+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
+destinations. The model will also replicate damage seen in the images.
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+## Technical Specifications [optional]
+
+#### Hardware
+
+The model was trained on two GTX 4090 for a duration of 2 days to extract 100 epochs of the model.
+
+#### Software
+
+The model was trained via the Kohya_SS gui.
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+## Model Card Contact
+
+Use the community section of this repository to contact me.