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--- |
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license: bigscience-bloom-rail-1.0 |
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--- |
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tags: |
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- stable-diffusion |
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- text-to-image |
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inference: false |
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--- |
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# Stable Diffusion v2 Model Card |
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This model card focuses on the model associated with the Stable Diffusion v2 model, available [here](https://github.com/Stability-AI/stablediffusion). |
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This `stable-diffusion-2` model is resumed from [stable-diffusion-2-base](https://huggingface.co/stabilityai/stable-diffusion-2-base) (`512-base-ema.ckpt`) and trained for 150k steps using a [v-objective](https://arxiv.org/abs/2202.00512) on the same dataset. Resumed for another 140k steps on `768x768` images. |
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- Use it with the [`stablediffusion`](https://github.com/Stability-AI/stablediffusion) repository: download the `768-v-ema.ckpt` [here](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/768-v-ema.ckpt). |
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- Use it with 🧨 [`diffusers`](https://huggingface.co/stabilityai/stable-diffusion-2#examples) |
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## Model Details |
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- **Developed by:** Robin Rombach, Patrick Esser |
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- **Model type:** Diffusion-based text-to-image generation model |
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- **Language(s):** English |
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- **License:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL) |
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- **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses a fixed, pretrained text encoder ([OpenCLIP-ViT/H](https://github.com/mlfoundations/open_clip)). |
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- **Resources for more information:** [GitHub Repository](https://github.com/Stability-AI/). |
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- **Cite as:** |
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@InProceedings{Rombach_2022_CVPR, |
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author = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn}, |
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title = {High-Resolution Image Synthesis With Latent Diffusion Models}, |
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booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
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month = {June}, |
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year = {2022}, |
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pages = {10684-10695} |
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} |
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## Examples |
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Using the [🤗's Diffusers library](https://github.com/huggingface/diffusers) to run Stable Diffusion 2 in a simple and efficient manner. |
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```bash |
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pip install --upgrade git+https://github.com/huggingface/diffusers.git transformers accelerate scipy |
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``` |
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Running the pipeline (if you don't swap the scheduler it will run with the default DDIM, in this example we are swapping it to EulerDiscreteScheduler): |
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