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Model: AI-ModelScope/sd-turbo
Source: Original Platform

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LICENSE

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+STABILITY AI NON-COMMERCIAL RESEARCH COMMUNITY LICENSE AGREEMENT        
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README.md

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+---
+pipeline_tag: text-to-image
+inference: false
+---
+
+# SD-Turbo Model Card
+
+<!-- Provide a quick summary of what the model is/does. -->
+![row01](output_tile.jpg)
+SD-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation.
+We release SD-Turbo as a research artifact, and to study small, distilled text-to-image models. For increased quality and prompt understanding, 
+we recommend [SDXL-Turbo](https://huggingface.co/stabilityai/sdxl-turbo/).
+
+## Model Details
+
+### Model Description
+SD-Turbo is a distilled version of [Stable Diffusion 2.1](https://huggingface.co/stabilityai/stable-diffusion-2-1), trained for real-time synthesis. 
+SD-Turbo is based on a novel training method called Adversarial Diffusion Distillation (ADD) (see the [technical report](https://stability.ai/research/adversarial-diffusion-distillation)), which allows sampling large-scale foundational 
+image diffusion models in 1 to 4 steps at high image quality. 
+This approach uses score distillation to leverage large-scale off-the-shelf image diffusion models as a teacher signal and combines this with an
+adversarial loss to ensure high image fidelity even in the low-step regime of one or two sampling steps. 
+
+- **Developed by:** Stability AI
+- **Funded by:** Stability AI
+- **Model type:** Generative text-to-image model
+- **Finetuned from model:** [Stable Diffusion 2.1](https://huggingface.co/stabilityai/stable-diffusion-2-1)
+
+### Model Sources
+
+For research purposes, we recommend our `generative-models` Github repository (https://github.com/Stability-AI/generative-models), 
+which implements the most popular diffusion frameworks (both training and inference).
+
+- **Repository:** https://github.com/Stability-AI/generative-models
+- **Paper:** https://stability.ai/research/adversarial-diffusion-distillation
+- **Demo [for the bigger SDXL-Turbo]:** http://clipdrop.co/stable-diffusion-turbo
+
+
+## Evaluation
+![comparison1](image_quality_one_step.png)
+![comparison2](prompt_alignment_one_step.png)
+The charts above evaluate user preference for SD-Turbo over other single- and multi-step models.
+SD-Turbo evaluated at a single step is preferred by human voters in terms of image quality and prompt following over LCM-Lora XL and LCM-Lora 1.5.
+
+**Note:** For increased quality, we recommend the bigger version [SDXL-Turbo](https://huggingface.co/stabilityai/sdxl-turbo/).
+For details on the user study, we refer to the [research paper](https://stability.ai/research/adversarial-diffusion-distillation).
+
+
+## Uses
+
+### Direct Use
+
+The model is intended for research purposes only. Possible research areas and tasks include
+
+- Research on generative models.
+- Research on real-time applications of generative models.
+- Research on the impact of real-time generative models.
+- Safe deployment of models which have the potential to generate harmful content.
+- Probing and understanding the limitations and biases of generative models.
+- Generation of artworks and use in design and other artistic processes.
+- Applications in educational or creative tools.
+
+Excluded uses are described below.
+
+### Diffusers
+
+```
+pip install diffusers transformers accelerate --upgrade
+```
+
+- **Text-to-image**:
+
+SD-Turbo does not make use of `guidance_scale` or `negative_prompt`, we disable it with `guidance_scale=0.0`.
+Preferably, the model generates images of size 512x512 but higher image sizes work as well.
+A **single step** is enough to generate high quality images.
+
+```py
+from diffusers import AutoPipelineForText2Image
+from modelscope import snapshot_download
+import torch
+
+local_dir = snapshot_download("AI-ModelScope/sd-turbo",revision='master')
+
+pipe = AutoPipelineForText2Image.from_pretrained(local_dir, torch_dtype=torch.float16, variant="fp16")
+pipe.to("cuda")
+
+prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe."
+image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+```
+
+- **Image-to-image**:
+
+When using SD-Turbo for image-to-image generation, make sure that `num_inference_steps` * `strength` is larger or equal 
+to 1. The image-to-image pipeline will run for `int(num_inference_steps * strength)` steps, *e.g.* 0.5 * 2.0 = 1 step in our example 
+below.
+
+```py
+from diffusers import AutoPipelineForImage2Image
+from diffusers.utils import load_image
+from modelscope import snapshot_download
+import torch
+
+local_dir = snapshot_download("AI-ModelScope/sd-turbo",revision='master')
+
+pipe = AutoPipelineForImage2Image.from_pretrained(local_dir, torch_dtype=torch.float16, variant="fp16")
+pipe.to("cuda")
+
+init_image = load_image(local_dir+"/cat.png").resize((512, 512))
+prompt = "cat wizard, gandalf, lord of the rings, detailed, fantasy, cute, adorable, Pixar, Disney, 8k"
+
+image = pipe(prompt, image=init_image, num_inference_steps=100, strength=0.5, guidance_scale=0.0).images[0]
+```
+
+### Out-of-Scope Use
+
+The model was not trained to be factual or true representations of people or events, 
+and therefore using the model to generate such content is out-of-scope for the abilities of this model.
+The model should not be used in any way that violates Stability AI's [Acceptable Use Policy](https://stability.ai/use-policy).
+
+## Limitations and Bias
+
+### Limitations
+- The quality and prompt alignment is lower than that of [SDXL-Turbo](https://huggingface.co/stabilityai/sdxl-turbo/).
+- The generated images are of a fixed resolution (512x512 pix), and the model does not achieve perfect photorealism.
+- The model cannot render legible text.
+- Faces and people in general may not be generated properly.
+- The autoencoding part of the model is lossy.
+
+
+### Recommendations
+
+The model is intended for research purposes only.
+
+## How to Get Started with the Model
+
+Check out https://github.com/Stability-AI/generative-models

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