Text-to-Image
Diffusers
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stable-diffusion
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LICENSE ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ STABILITY AI NON-COMMERCIAL RESEARCH COMMUNITY LICENSE AGREEMENT
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+ Dated: December 06, 2023
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+ c. If you distribute or make the Software Products, or any Derivative Works thereof, available to a third party, the Software Products, Derivative Works, or any portion thereof, respectively, will remain subject to this Agreement and you must (i) provide a copy of this Agreement to such third party, and (ii) retain the following attribution notice within a "Notice" text file distributed as a part of such copies: "This Stability AI Model is licensed under the Stability AI Non-Commercial Research Community License, Copyright (c) Stability AI Ltd. All Rights Reserved.” If you create a Derivative Work of a Software Product, you may add your own attribution notices to the Notice file included with the Software Product, provided that you clearly indicate which attributions apply to the Software Product and you must state in the NOTICE file that you changed the Software Product and how it was modified.
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+ 2. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE SOFTWARE PRODUCTS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE SOFTWARE PRODUCTS, DERIVATIVE WORKS OR ANY OUTPUT OR RESULTS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE SOFTWARE PRODUCTS, DERIVATIVE WORKS AND ANY OUTPUT AND RESULTS.
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+ 3. Limitation of Liability. IN NO EVENT WILL STABILITY AI OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY DIRECT, INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF STABILITY AI OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.
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+ 4. Intellectual Property.
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+ a. No trademark licenses are granted under this Agreement, and in connection with the Software Products or Derivative Works, neither Stability AI nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Software Products or Derivative Works.
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+ b. Subject to Stability AI’s ownership of the Software Products and Derivative Works made by or for Stability AI, with respect to any Derivative Works that are made by you, as between you and Stability AI, you are and will be the owner of such Derivative Works
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+ c. If you institute litigation or other proceedings against Stability AI (including a cross-claim or counterclaim in a lawsuit) alleging that the Software Products, Derivative Works or associated outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Stability AI from and against any claim by any third party arising out of or related to your use or distribution of the Software Products or Derivative Works in violation of this Agreement.
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+ 5. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Software Products and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Stability AI may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of any Software Products or Derivative Works. Sections 2-4 shall survive the termination of this Agreement.
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+ 6. Governing Law. This Agreement will be governed by and construed in accordance with the laws of the United States and the State of California without regard to choice of law
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+ principles.
README.md ADDED
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+ ---
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+ license: other
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+ license_name: stabilityai-nc-research-community
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+ license_link: LICENSE
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+ tags:
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+ - text-to-image
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+ - stable-diffusion
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+ - diffusers
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+ extra_gated_prompt: >-
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+ By clicking "Agree", you agree to the [License
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+ Agreement](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE)
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+ and acknowledge Stability AI's [Privacy
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+ Policy](https://stability.ai/privacy-policy).
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+ extra_gated_fields:
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+ Name: text
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+ Email: text
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+ Country: country
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+ Organization or Affiliation: text
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+ Receive email updates and promotions on Stability AI products, services, and research?:
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+ type: select
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+ options:
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+ - 'Yes'
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+ - 'No'
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+ I acknowledge that this model is for non-commercial use only unless I acquire a separate license from Stability AI: checkbox
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+ language:
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+ - en
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+ pipeline_tag: text-to-image
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+ ---
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+ # Stable Diffusion 3 Medium
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+ ![sd3 demo images](sd3demo.jpg)
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+
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+ ## Model
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+
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+ ![mmdit](mmdit.png)
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+
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+ [Stable Diffusion 3 Medium](https://stability.ai/news/stable-diffusion-3-medium) is a Multimodal Diffusion Transformer (MMDiT) text-to-image model that features greatly improved performance in image quality, typography, complex prompt understanding, and resource-efficiency.
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+
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+ For more technical details, please refer to the [Research paper](https://stability.ai/news/stable-diffusion-3-research-paper).
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+
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+ Please note: this model is released under the Stability Non-Commercial Research Community License. For a Creator License or an Enterprise License visit Stability.ai or [contact us](https://stability.ai/license) for commercial licensing details.
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+
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+
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+
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+ ### Model Description
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+
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+ - **Developed by:** Stability AI
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+ - **Model type:** MMDiT text-to-image generative model
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+ - **Model Description:** This is a model that can be used to generate images based on text prompts. It is a Multimodal Diffusion Transformer
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+ (https://arxiv.org/abs/2403.03206) that uses three fixed, pretrained text encoders
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+ ([OpenCLIP-ViT/G](https://github.com/mlfoundations/open_clip), [CLIP-ViT/L](https://github.com/openai/CLIP/tree/main) and [T5-xxl](https://huggingface.co/google/t5-v1_1-xxl))
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+
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+ ### License
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+
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+ - **Non-commercial Use:** Stable Diffusion 3 Medium is released under the [Stability AI Non-Commercial Research Community License](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE). The model is free to use for non-commercial purposes such as academic research.
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+ - **Commercial Use**: This model is not available for commercial use without a separate commercial license from Stability. We encourage professional artists, designers, and creators to use our Creator License. Please visit https://stability.ai/license to learn more.
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+
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+
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+ ### Model Sources
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+
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+ For local or self-hosted use, we recommend [ComfyUI](https://github.com/comfyanonymous/ComfyUI) for inference.
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+
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+ Stable Diffusion 3 Medium is available on our [Stability API Platform](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post).
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+
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+ Stable Diffusion 3 models and workflows are available on [Stable Assistant](https://stability.ai/stable-assistant) and on Discord via [Stable Artisan](https://stability.ai/stable-artisan).
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+
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+ - **ComfyUI:** https://github.com/comfyanonymous/ComfyUI
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+ - **StableSwarmUI:** https://github.com/Stability-AI/StableSwarmUI
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+ - **Tech report:** https://stability.ai/news/stable-diffusion-3-research-paper
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+ - **Demo:** https://huggingface.co/spaces/stabilityai/stable-diffusion-3-medium
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+ - **Diffusers support:** https://huggingface.co/stabilityai/stable-diffusion-3-medium-diffusers
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+
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+
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+ ## Training Dataset
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+
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+ We used synthetic data and filtered publicly available data to train our models. The model was pre-trained on 1 billion images. The fine-tuning data includes 30M high-quality aesthetic images focused on specific visual content and style, as well as 3M preference data images.
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+
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+ ## File Structure
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+ ```
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+ ├── comfy_example_workflows/
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+ │ ├── sd3_medium_example_workflow_basic.json
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+ │ ├── sd3_medium_example_workflow_multi_prompt.json
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+ │ └── sd3_medium_example_workflow_upscaling.json
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+
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+ ├── text_encoders/
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+ │ ├── README.md
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+ │ ├── clip_g.safetensors
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+ │ ├── clip_l.safetensors
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+ │ ├── t5xxl_fp16.safetensors
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+ │ └── t5xxl_fp8_e4m3fn.safetensors
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+
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+ ├── LICENSE
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+ ├── sd3_medium.safetensors
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+ ├── sd3_medium_incl_clips.safetensors
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+ ├── sd3_medium_incl_clips_t5xxlfp8.safetensors
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+ └── sd3_medium_incl_clips_t5xxlfp16.safetensors
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+
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+ ```
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+
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+ We have prepared three packaging variants of the SD3 Medium model, each equipped with the same set of MMDiT & VAE weights, for user convenience.
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+
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+ * `sd3_medium.safetensors` includes the MMDiT and VAE weights but does not include any text encoders.
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+ * `sd3_medium_incl_clips_t5xxlfp16.safetensors` contains all necessary weights, including fp16 version of the T5XXL text encoder.
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+ * `sd3_medium_incl_clips_t5xxlfp8.safetensors` contains all necessary weights, including fp8 version of the T5XXL text encoder, offering a balance between quality and resource requirements.
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+ * `sd3_medium_incl_clips.safetensors` includes all necessary weights except for the T5XXL text encoder. It requires minimal resources, but the model's performance will differ without the T5XXL text encoder.
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+ * The `text_encoders` folder contains three text encoders and their original model card links for user convenience. All components within the text_encoders folder (and their equivalents embedded in other packings) are subject to their respective original licenses.
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+ * The `example_workfows` folder contains example comfy workflows.
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+
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+ ## Using with Diffusers
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+
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+ Make sure you upgrade to the latest version of diffusers: pip install -U diffusers. And then you can run:
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+
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+ ```python
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+ import torch
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+ from diffusers import StableDiffusion3Pipeline
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+
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+ pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16)
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+ pipe = pipe.to("cuda")
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+
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+ image = pipe(
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+ "A cat holding a sign that says hello world",
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+ negative_prompt="",
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+ num_inference_steps=28,
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+ guidance_scale=7.0,
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+ ).images[0]
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+ image
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+ ```
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+
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+ Refer to [the documentation](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/stable_diffusion_3) for more details on optimization and image-to-image support.
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+
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+ ## Uses
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+
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+ ### Intended Uses
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+
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+ Intended uses include the following:
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+ * Generation of artworks and use in design and other artistic processes.
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+ * Applications in educational or creative tools.
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+ * Research on generative models, including understanding the limitations of generative models.
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+
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+ All uses of the model should be in accordance with our [Acceptable Use Policy](https://stability.ai/use-policy).
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+
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+ ### Out-of-Scope Uses
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+
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+ The model was not trained to be factual or true representations of people or events. As such, using the model to generate such content is out-of-scope of the abilities of this model.
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+
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+ ## Safety
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+
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+ As part of our safety-by-design and responsible AI deployment approach, we implement safety measures throughout the development of our models, from the time we begin pre-training a model to the ongoing development, fine-tuning, and deployment of each model. We have implemented a number of safety mitigations that are intended to reduce the risk of severe harms, however we recommend that developers conduct their own testing and apply additional mitigations based on their specific use cases.
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+ For more about our approach to Safety, please visit our [Safety page](https://stability.ai/safety).
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+
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+ ### Evaluation Approach
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+
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+ Our evaluation methods include structured evaluations and internal and external red-teaming testing for specific, severe harms such as child sexual abuse and exploitation, extreme violence, and gore, sexually explicit content, and non-consensual nudity. Testing was conducted primarily in English and may not cover all possible harms. As with any model, the model may, at times, produce inaccurate, biased or objectionable responses to user prompts.
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+
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+ ### Risks identified and mitigations:
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+
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+ * Harmful content: We have used filtered data sets when training our models and implemented safeguards that attempt to strike the right balance between usefulness and preventing harm. However, this does not guarantee that all possible harmful content has been removed. The model may, at times, generate toxic or biased content. All developers and deployers should exercise caution and implement content safety guardrails based on their specific product policies and application use cases.
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+ * Misuse: Technical limitations and developer and end-user education can help mitigate against malicious applications of models. All users are required to adhere to our Acceptable Use Policy, including when applying fine-tuning and prompt engineering mechanisms. Please reference the Stability AI Acceptable Use Policy for information on violative uses of our products.
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+ * Privacy violations: Developers and deployers are encouraged to adhere to privacy regulations with techniques that respect data privacy.
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+
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+ ### Contact
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+
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+ Please report any issues with the model or contact us:
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+
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+ * Safety issues: safety@stability.ai
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+ * Security issues: security@stability.ai
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+ * Privacy issues: privacy@stability.ai
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+ * License and general: https://stability.ai/license
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+ * Enterprise license: https://stability.ai/enterprise
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