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--- |
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license: creativeml-openrail-m |
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library_name: diffusers |
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tags: |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- diffusers |
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- diffusers-training |
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- lora |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- diffusers |
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- diffusers-training |
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- lora |
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base_model: runwayml/stable-diffusion-v1-5 |
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inference: true |
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--- |
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# LoRA text2image fine-tuning - animanatwork/illustrations-lora |
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These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the animanatwork/text_to_image_dataset dataset. |
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Below, we can find some images from the dataset: |
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<div style="display: flex; justify-content: space-between;"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/66297c313291276a14318d23/fHCi3t9AlK5AasMt_K0nh.png" width="30%" /> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/66297c313291276a14318d23/fYdTOG8QKtUHKvDOBw40r.png" width="30%" /> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/66297c313291276a14318d23/IXx2U6cM0SH4CFGw1qmjE.png" width="30%" /> |
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</div> |
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The images below are generated from the model using the prompt: "a stylized illustration of a woman sitting in a comfortable chair, reading a book. She is wearing a hat, and her expression appears focused and calm. A black cat is also depicted, sitting beside her and looking at the book, suggesting a shared moment of quiet and companionship. The woman is dressed in a casual outfit with yellow shoes, and the overall color scheme is simple, using black, white, and yellow. The setting seems cozy and peaceful, ideal for reading." |
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<div style="display: flex; justify-content: space-between;"> |
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<img src="./image_0.png" width="25%" /> |
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<img src="./image_1.png" width="25%" /> |
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<img src="./image_2.png" width="25%" /> |
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<img src="./image_3.png" width="25%" /> |
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</div> |
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## Intended uses & limitations |
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Do NOT use in production. This model was purely created for research purposes. |
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#### How to use |
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```python |
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# TODO: add an example code snippet for running this diffusion pipeline |
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``` |
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#### Limitations and bias |
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[TODO: provide examples of latent issues and potential remediations] |
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## Training details |
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- The model was trained on the "animanatwork/text_to_image_dataset" dataset using 10_000 training step (default is 15_000) and took several hours to train. For more details see [Colab notebook](https://colab.research.google.com/drive/1CePJWR2sfYW-w0oPuiIdJzuc82Z6yYHt#scrollTo=QzKEQJYkUv2Q). |
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- The dataset's tokens were generated using chatGPT vision. During training, I noticed CLIP can only use 77 tokens for a given image. Since most of our image descriptions contained more tokens, we'll have to create a new dataset that doesn't exceed the maximum. |
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[TODO: describe the data used to train the model] |
