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The Ultimate Guide to SDXL Prompts

by miroslavar
written by miroslavar

What is Stable Diffusion XL?

Stable Diffusion, or SD for short, is a groundbreaking technology that has revolutionized the way we generate AI-based images. SDXL takes this a step further by offering generation in 1024 resolution, providing an unparalleled level of detail. Essentially, it’s the same stable diffusion you know and love, but with a lot more pixels to play with.

What Makes a Good Stable Diffusion Prompt?

Creating a good Stable Diffusion prompt is both an art and a science. The prompt should be clear, concise, and specific. Vague or overly complex prompts can lead to unexpected or unsatisfactory results. The key is to guide the AI in a direction that aligns with your vision, without stifling its creative potential.

How Do You Weight Stable Diffusion Prompts?

Weighting in Stable Diffusion prompts is a way to prioritize certain aspects of the generated image. By assigning different weights to different parts of the prompt, you can influence the AI’s focus. For example, if you want the AI to pay more attention to the background than the foreground, you could weight the background prompt more heavily.

Mastering the Art of Weighted Prompts: Examples and Outcomes

Weighted Prompt Example 1:

**Prompt:** “A portrait of a woman with curly hair {weight: 0.7}, smiling {weight: 0.5}, against a backdrop of cherry blossoms {weight: 0.8}.”

**Expected Result:** The AI will prioritize the backdrop of cherry blossoms (0.8) over the woman’s curly hair (0.7) and her smile (0.5). You’ll get a detailed background filled with cherry blossoms, a woman with curly hair, and a smile, but the focus will be more on the background.

Weighted Prompt Example 2:

**Prompt:** “A woman in her 30s {weight: 0.3} wearing a vintage 1920s flapper dress {weight: 0.9}, looking confidently into the camera {weight: 0.6}.”

**Expected Result:** The AI will focus heavily on the vintage 1920s flapper dress (0.9), followed by her confident look (0.6), and less on her being in her 30s (0.3). The resulting image will likely feature a very detailed flapper dress, with a confident expression on the woman’s face.

Weighted Prompt Example 3:

**Prompt:** “A black-and-white portrait {weight: 0.8} of a woman with short hair {weight: 0.5}, wearing a leather jacket {weight: 0.7}, exuding a rebellious vibe {weight: 0.6}.”

**Expected Result:** The black-and-white aspect of the portrait will be the most prominent feature (0.8), followed by the leather jacket (0.7) and the rebellious vibe (0.6). The woman’s short hair will be the least emphasized element (0.5). The image will be a striking black-and-white portrait, with a focus on the leather jacket and a rebellious atmosphere.

Weighted Prompt Example 4:

**Prompt:** “A woman {weight: 0.2} in a sunflower field {weight: 0.9} during sunset {weight: 0.8}.”

**Expected Result:** The AI will focus primarily on the sunflower field (0.9) and the sunset (0.8), with less emphasis on the woman (0.2). The resulting image will likely be a breathtaking landscape of a sunflower field bathed in the golden light of the setting sun, with a woman present but not as the main focus.

Weighted prompts allow for nuanced control over the AI’s focus, enabling you to create images that emphasize the elements most important to you. By understanding how to effectively use weights, you can fine-tune your prompts to get precisely the results you desire.

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What is an Example of a Good Stable Diffusion Prompt?

A good Stable Diffusion prompt could be something like “A serene lakeside at sunset with vibrant colors reflecting in the water.” This prompt is specific enough to guide the AI but leaves room for creative interpretation. 

# Crafting the Perfect Image Prompt for Women’s Portraits: Good vs. Bad Examples

Good Prompt Example 1: 

**Prompt:** “A close-up portrait of a woman with curly brown hair, smiling, with a soft-focus background of cherry blossoms.”

**Expected Result:** The AI will generate a detailed close-up portrait focusing on a woman with curly brown hair. She will be smiling, and the background will feature cherry blossoms in soft focus, adding a dreamy, ethereal quality to the image.

Bad Prompt Example 1:

**Prompt:** “A woman.”

**Expected Result:** This prompt is too vague and could result in any kind of image featuring a woman. There’s no guidance on the setting, mood, or any specific features, leading to unpredictable and likely unsatisfactory results.

Good Prompt Example 2:

**Prompt:** “A woman in her 30s wearing a vintage 1920s flapper dress, looking confidently into the camera against a backdrop of a jazz club.”

**Expected Result:** The AI will generate an image of a woman in her 30s, dressed in a 1920s flapper outfit. She will be looking confidently into the camera, and the background will depict the ambiance of a jazz club, complete with instruments and perhaps some patrons.

Bad Prompt Example 2:

**Prompt:** “A woman in a dress.”

**Expected Result:** Again, this prompt is too general. The AI has no information on the type of dress, the setting, or the mood you’re aiming for. You’ll likely get a random image of a woman in some kind of dress, but it may not meet your specific needs.

Good Prompt Example 3:

**Prompt:** “A black-and-white portrait of a woman with short hair, wearing a leather jacket, exuding a rebellious vibe.”

**Expected Result:** The AI will generate a black-and-white image capturing a woman with short hair and a leather jacket. The mood will be rebellious, perhaps with a smoky or gritty background to enhance the vibe.

Bad Prompt Example 3:

**Prompt:** “A woman in black and white.”

**Expected Result:** This prompt is not specific enough to guide the AI effectively. While you may get a black-and-white image of a woman, there’s no telling what her appearance or the mood of the image will be.

By crafting specific, descriptive prompts, you can guide the AI to generate images that closely align with your vision. On the other hand, vague prompts often lead to unpredictable and unsatisfactory results. The key is to find the right balance between specificity and creative freedom.

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What is Positive and Negative Prompt in Stable Diffusion?

Positive prompts guide the AI towards what you want to see in the generated image, while negative prompts specify what you want to avoid. For instance, a positive prompt might be “lush greenery,” and a negative prompt could be “no buildings.” This would instruct the AI to focus on natural elements while avoiding any man-made structures.

Does Stable Diffusion Allow NSFW?

Stable Diffusion technology itself doesn’t inherently restrict content, but it’s crucial to adhere to the guidelines and policies of the platform you’re using. Most platforms have strict rules against generating NSFW (Not Safe For Work) content.

What is Stable Diffusion Prompts with Seeds?

Seeds in Stable Diffusion are essentially unique identifiers that ensure the reproducibility of a generated image. By using the same seed with the same prompt, you can generate the same image multiple times. This is particularly useful for fine-tuning and iterative design processes.

User Interfaces for Stable Diffusion

Artbreeder

Artbreeder is an online platform that allows users to create and explore images generated through Stable Diffusion and other algorithms. It offers a user-friendly interface and various customization options.

Runway

Runway is another online service that provides access to Stable Diffusion models. It is geared towards artists and designers and offers a more professional set of tools.

DeepArt

DeepArt is a web-based application that uses Stable Diffusion for style transfer. It allows users to upload an image and choose a style to apply to it.

Local Installs

ComfyUI and Automatic1111: Pioneering Tools for Stable Diffusion

ComfyUI: A User-Friendly Interface for AI

ComfyUI is a graphical user interface designed to make it easier for users to interact with various AI models, including Stable Diffusion. The tool aims to simplify the complexities of AI algorithms, offering a more intuitive way to generate images or perform other tasks. With its drag-and-drop features and user-friendly controls, ComfyUI is ideal for those who may not have a technical background but still want to explore the capabilities of Stable Diffusion.

ComfyUI often comes with pre-configured settings for Stable Diffusion, allowing users to generate high-quality images with minimal effort. Users can easily adjust parameters like resolution, sampling steps, and other variables to fine-tune the output.

Automatic1111: A Versatile Local Tool

Automatic1111 is a more advanced tool that is generally used locally on a user’s machine. It offers a wide range of customization options and is geared towards those who have a deeper understanding of AI algorithms. Automatic1111 allows users to load different AI models, including Stable Diffusion, and offers more granular control over the generation process.

Automatic1111 is particularly useful for Stable Diffusion as it allows for a high degree of customization. Users can input specific prompts, adjust weights, and even use seeds to generate unique images. The tool also supports batch processing, making it easier to produce multiple images in a single run.

Both ComfyUI and Automatic1111 serve as valuable tools in the realm of Stable Diffusion, catering to different user needs. Whether you’re a beginner looking for a simple interface or an advanced user seeking more control, these tools offer something for everyone.

Online Services

Google Colab

Google Colab is a popular choice for running Stable Diffusion algorithms. It offers free GPU resources and is accessible through a web browser.

AWS and Azure

Cloud services like AWS and Azure offer more robust solutions for running Stable Diffusion algorithms but come at a cost.

DeepArt Premium

DeepArt offers a premium service that allows for higher-resolution images and faster processing times.

Runway Subscription

Runway offers a subscription model that provides additional features like batch processing and higher-quality outputs.

By understanding the various tools and platforms available for Stable Diffusion, you can choose the one that best suits your needs, whether you’re a casual user or a professional looking for more advanced options.

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Unveiling the Power of Stable Diffusion XL Model

by miroslavar
written by miroslavar

The Stable Diffusion XL (SDXL) model is revolutionizing the way we perceive AI-generated art. With its unparalleled attention to detail, natural lighting, and realistic textures, this model is a game-changer for artists and AI enthusiasts alike. Let’s dive into the intricacies of this groundbreaking technology.

A New Level of Realism: What Sets SDXL Apart

The SDXL model, also known as Epic Realism, offers a level of detail that is nothing short of astonishing. From the intricate folds of fabric to the natural play of light and shadow, the model captures the essence of realism in a way that was previously unattainable. The model’s focus is not on creating the perfect studio photo but on emulating the kind of snapshots you would take with your phone—authentic, natural, and incredibly lifelike.

Dynamic Posing and Natural Light: A Closer Look

One of the standout features of the SDXL model is its ability to create dynamic poses that look incredibly natural. The model also excels in replicating natural light, avoiding the artificial look of studio lighting. The result is a more authentic representation of everyday life, captured in a snapshot.

The Texture Game: Achieving Authenticity

What really sets the SDXL model apart is its ability to replicate skin texture with astonishing accuracy. From fine hairs to subtle imperfections and even the natural oiliness of the skin, the model captures it all. This level of detail is particularly challenging for AI to achieve, making the SDXL model a significant advancement in the field.

The Technicalities: Sampler and Upscale Settings

To get the most out of the SDXL model, it’s crucial to use the right settings. The recommended sampler is the DPM sampler, and for upscaling, the 4X MKD Super Scale is advised. These settings ensure that you achieve the highest level of detail and realism possible. 

stable diffusion sdxl realism model

Additional Tools: Lora and Extensions

The model also supports various extensions and tools to enhance the final output. One such tool is the Epic Realism Helper lora, which can be downloaded and added to your positive prompt in the interface. This lora can significantly improve the lighting and details, making the image even more realistic.

Versatility: Beyond Modern Characters

While the model excels in creating modern characters, its capabilities are not limited to that. From historical figures like Viking women to sci-fi inspired characters in metal armor, the SDXL model can do it all. The focus remains on authenticity, regardless of the subject matter.

Final Thoughts: The Future of AI-Generated Art

The Stable Diffusion XL model is a monumental step forward in the realm of AI-generated art. Its focus on authenticity and attention to detail sets it apart from other models, making it a valuable tool for artists and AI enthusiasts. As technology continues to advance, models like SDXL are paving the way for a future where AI-generated art is indistinguishable from human-created art.

The Impact on Real Photographers: A Personal Take

As someone deeply invested in the intersection of art and technology, I can’t help but ponder the implications of AI-generated realism on the world of professional photography. The SDXL model’s ability to replicate natural lighting, intricate details, and even the texture of human skin is awe-inspiring. But what does this mean for real photographers?

In my opinion, while AI models like SDXL offer an unprecedented level of realism, they are not a replacement for the human touch that comes with professional photography. Photographers bring not just technical skills but also a unique artistic vision, emotional intelligence, and the ability to capture the “decisive moment” that AI currently can’t replicate. 

However, the rise of AI-generated realism could serve as a tool rather than a threat. Photographers could use these advanced models for initial drafts or to explore creative ideas before executing them in the real world. It could also open doors for collaborations between AI and human artists, leading to a new genre of art that we haven’t yet imagined.

That said, the advent of such advanced AI models could also lead to market saturation, where the line between AI-generated and human-created art begins to blur. This could potentially devalue the work of real photographers, especially those just starting in the field.

In conclusion, while AI-generated realism is an exciting advancement, it’s essential for us to approach it as a complementary tool rather than a replacement for human creativity and skill. The future could very well be a collaborative one, where AI and human artists work in tandem to create something truly extraordinary.

The Stable Diffusion XL (SDXL) model is redefining the boundaries of AI-generated art with its unparalleled realism and attention to detail. From natural lighting to authentic textures, this model is a game-changer. Discover how the SDXL model is shaping the future of AI art.

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AI News

Stable diffusion XL 1.0: A Revolution in AI-Driven Digital Art

by miroslavar
written by miroslavar

The release of SDXL 1.0 by Stability AI. The release was unexpected and was first noticed on a Hacker News aggregator. Stability AI then announced they would discuss the release on their Discord live, highlighting the differences and modifications made from the previous version, SDXL 0.9. Shortly after, all the weights for SDXL 1.0 became available on HuggingFace. Stable diffusion XL 1.0 is comparable in quality to mid Journey 5 but stands out due to the array of tools available for it and its licensing terms. Users can now use it commercially without restrictions, fine-tune it on their own datasets, and use it for more than just text. It can be integrated with various models and algorithms to produce impressive outputs, especially beneficial for those in the CGI or 3D modeling fields. The performance of SDXL 1.0 is highlighted as being superior, and it’s less pre-censored than other models.

Ahmad, from Stability AI, had previously been cautious about discussing the plans for SDXL 1.0. A significant part of their decision-making was influenced by feedback from researchers. Interestingly, the leak of the weights might have expedited the release process.  Stability AI claims that SDXL 1.0 is their best image model and has been tested against various other models. The results indicate that people prefer images generated by SDXL over other models.

Ahmad has emphasized that SDXL is not just about generating images. It’s about transferring styles, applying layers, and doing so in a way that appears cohesive and realistic to the human eye. Photorealism is becoming a competitive feature that’s continuously improving. SDXL can generate content that’s typically challenging for image models, such as hands, text, or spatially arranged compositions. These compositions are aware of depth of field, focal points, lighting perspectives, and atmospheric scattering. Technically, SDXL 1.0 is one of the largest open-access image models available. It consists of a 3.5 billion parameter base model and a 6.6 billion parameter refiner. The two-stage architecture ensures robust image generation without compromising speed or requiring excessive compute resources. This design allows it to run efficiently on consumer GPUs with limited VRAM.

Fine-tuning with stable diffusion XL 1.0 is easier than ever. Most of the process involves data wrangling rather than complex coding. Stability AI claims that fine-tuning SDXL, even with diverse input images, is straightforward.

Introduction The digital art landscape is undergoing a significant transformation, thanks to advancements in artificial intelligence. One of the most notable developments in this realm is the release of Stable Diffusion 1.0, a cutting-edge tool that promises to redefine the boundaries of AI art.

Harnessing the Power of Amazon Infrastructure 

Stable Diffusion 1.0 has seamlessly integrated with Amazon’s infrastructure, specifically SageMaker and Bedrock. This strategic collaboration ensures that artists and developers can access and utilize the tool with ease, especially if they are already embedded within Amazon’s ecosystem.

Innovative Text Integration in Art One of the standout features of Stable Diffusion 1.0 is its ability to flawlessly integrate text into images. This capability opens up a plethora of opportunities for artists to create multi-dimensional pieces, where text and visuals coalesce to tell a compelling story. The tool’s adeptness at handling multiple focal points within a single frame is truly commendable, allowing for intricate compositions that captivate the viewer.

Visual capabilities of stable diffusion XL 1.0

Character Portraits Come to Life 

Stable Diffusion 1.0 shines exceptionally well in the realm of character portraits. The tool can meticulously differentiate between skin tones, clothing textures, and even handle refractions. The result? Lifelike portraits that resonate with realism and depth, making it a valuable asset for digital artists aiming for photorealism in their work.

Abstract Artistry with Precision 

For those who lean towards abstract and cyberpunk styles, stable diffusion XL 1.0 does not disappoint. The tool’s capability to generate intricate line art with minimalist color palettes ensures that artists can bring their most avant-garde visions to life. The clarity with which the tool delineates between different elements within a composition is a testament to its advanced AI capabilities.

Redefining Food Art 

In the realm of food art, Stable Diffusion 1.0 sets a new benchmark. Whether it’s capturing the greasy texture of fries or the gooey consistency of cheese, the tool renders each element with unparalleled accuracy. This precision ensures that each dish is not just visually appetizing but also resonates with authenticity.

Stable diffusion XL 1.0 is undeniably a game-changer in the world of AI-driven digital art. Its advanced features, combined with its seamless integration with Amazon’s infrastructure, make it an indispensable tool for modern artists. As the boundaries between technology and art continue to blur, tools like Stable Diffusion 1.0 will undoubtedly lead the charge, shaping the future of digital artistry.

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Mind-Blowing Stable Diffusion XL 0.9 Trick Revealed

by miroslavar
written by miroslavar

Stable Diffusion XL 0.9, an AI model used for generating high-quality images, has recently received an update that allows it to be used with version 1.5 models. Prior to this update, the base model of SDXL (version 0.9) had limitations in creating realistic and aesthetically pleasing faces. The faces generated using the base model appeared strange and the overall composition of the facial anatomy was off.

To overcome these limitations, a workflow was developed by taking a prompt and inputting it into the base model of SDXL along with a latent code. This generated an initial image, which was then refined by inputting it into the refiner model of SDXL. The refiner model made use of a different model than the base model, resulting in an improved image. The refinement process involved adding noise to the image to make it cleaner, followed by a face restoration step. The final result was a face that looked significantly better than the initial one.

What can version 1.5 do for your artwork

An example was provided to showcase the effectiveness of this workflow. The initial image generated by the base model of SDXL had a wonky face with strange anatomical features. However, after putting it through the version 1.5 model, the issues were resolved, and the face looked much better. This demonstrated the potential of this workflow in improving the quality of generated images.

The example workflow also mentioned an expanded workflow that used both SDXL and version 1.5 models. Although the workflow was not refined and appeared messy, it showed promise in enhancing the generated images. This expanded workflow involved taking an image from SDXL, adding noise to it, and then using a virtual version 1.5 model to further improve the image. The results were promising, with better facial and chest anatomy observed.

Comparisons between images generated using only SDXL and those generated using version 1.5 illustrated the improvements achieved. The facial anatomy, especially the eyes, looked strange in the SDXL-only images. However, once they were put through the version 1.5 model, the facial features became more defined and realistic. While there were still some issues with facial anatomy, the images generated using version 1.5 were significantly better than the base model.

In conclusion, the integration of Stable Diffusion XL 0.9 with version 1.5 models has shown great potential in improving the quality of generated images. The workflow involving the base and refiner models of SDXL, along with the addition of noise and face restoration, has led to noticeable improvements. The expanded workflow using both SDXL and version 1.5 models is still being refined but has shown promise. With further adjustments and experimentation, this integration could result in even better and more realistic generated images.

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Notably, the age of the characters created with SDXL 1.0 did not correspond with the artist’s original intentions. For instance, when aiming to create a young woman in her 20s, the resulting image seemed to depict a woman in her 30s or 40s. The artist found that by using the SDXL 1.5 model, the facial quality and overall image improved significantly, rendering a more accurate representation of a youthful character.

Despite this progress, further enhancements are still required. The video example pointed out several areas where the SDXL software could be improved. One example is the representation of the iris in the eyes, which appeared distorted and unrealistic when using the SDXL 1.0 model. However, when the image was processed with the SDXL 1.5 model, the overall quality of the facial features improved, suggesting that the technology is evolving.

Another challenge the example encountered was the need to upscale the images to 4K resolution. To achieve this, they relied on a multi-diffusion upscaling technique from 1080p to 4K. While this step proved to be effective, it added an extra layer of complexity to the overall workflow.

Moreover, the example mentioned that the base model of SDXL was not usable for their purposes, as it resulted in strange-looking faces with distorted anatomical features. This limitation indicates that further refinement is needed to ensure accurate and realistic representations. Using SDXL with custom models would be more suitable once fine-tuned versions become available. Customized models will be released soon, allowing for more precise and polished artwork.

Despite these challenges and limitations, we can be hopeful about the future of SDXL. Examples of improved facial compositions and the workflow using the SDXL 1.5 model, combined with upscaling, produced desirable results. Stable Diffusion XL 0.9 shows promise as an innovative tool for AI art. Although there are still areas requiring improvement, such as facial distortion and anatomical accuracy, the advancements made in the SDXL 1.5 model are encouraging. Artists anticipate the release of fine-tuned custom models and look forward to utilizing SDXL to create stunning and realistic artwork.

excerpt: The emerging field of AI art has witnessed another significant advancement with the introduction of Stable Diffusion XL 0.9. This cutting-edge technology utilizes deep learning algorithms to generate highly realistic images of human faces. However, while there are still some shortcomings to be addressed, the results obtained from SDXL 1.5 are encouraging.

Stable Diffusion XL 0.9 has received an update that enables it to be used with version 1.5 models, resulting in improved image quality. The initial results generated using the base model of SDXL showed strange facial anatomy, but refinement through the addition of noise and face restoration using the refiner model produced significantly better results. An expanded workflow combining SDXL and version 1.5 further enhanced image quality. Future adjustments and experimentation could lead to even more realistic generated images.

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AI Vlogs announces Stable Diffusion XL 0.9 Update

by miroslavar
written by miroslavar

AI Vlogs has recently announced a new update to their stable diffusion XL model that they have called version 0.9. This update has several impressive features that are expected to generate the ability to generate hyper-realistic creations for films and advancements in design and industrial use. Its direct paid competition of MidJourney.

Announcement by Stability AI

Stability AI has become very product-focused, which has helped them to sharpen their approach to safety and generate new models. The new version of stable diffusion XL is available today in clip drop. They are pushing it very hard, and the API is coming soon.

Improvements included in the update

There are several significant improvements included in the Stable Diffusion XL 0.9 update that are worth noting:

  • Improvements in depth of field, color gamut, and how much color the model is comfortable expressing in any given generation
  • Context awareness of faces and organic shapes, such as hands
  • Vastly improved text rendering
  • Enhancements in the image-to-image prompting, in-painting, and out-painting functionalities
  • Additionally, Stable Diffusion XL 0.9 has one of the largest parameter counts of any open-source image model, with 3.5 billion parameters in the base model and 6.6 billion parameters in The Ensemble Pipeline. The final output is created by running on two models and aggregating the results.

One of the key features of SDXL 0.9 is its natural language processing capabilities, which allow users to input prompts using regular language. For instance, it can generate an image of “glowing jellyfish floating through a foggy Forest at Twilight” or a “Frozen castle made entirely of ice cream in a Land of cotton candy clouds and lollipop trees” just by using natural language prompts. This is a vast improvement over the older version (1.5), which requires single or two-word prompts separated by commas, and even model weights to generate AI art.

Stunning Composition Despite Base Model

Despite being just a base model, SDXL 0.9 can still produce stunning compositions. Even though image fidelity is not perfect yet, the quality of the images is impressive. For example, it generated an image of a yellow train with surreal elements, a Jedi female fighting Darth Vader, and a woman eating ice cream. While there are minor issues with extra limbs or imperfect hands, the resulting images are still impressive, especially considering that these were created using only natural language prompts.

Compatibility

Stable Diffusion XL 0.9 is compatible with Linux users with compatible AMD cards that have 16GB of VRAM. However, NVIDIA GPUs are still recommended, and the model will run on modern consumer GPUs. SDXL 0.9 is the most advanced development in the stable diffusion text-to-image suite of models, boasting the largest parameter count of any open-source image model to date. It uses a 3.5-billion-parameter base model and a 6.6-billion-parameter model ensemble pipeline that aggregates the results of two models running in parallel.

Availability

Clip drop has made this product available, and an open-source release is expected mid-July. The Stability AI interface has made it very easy for developers to provide low or no-cost updates to their user base. Stability AI is committed to researching how AI can benefit, rather than replace, human interactions. Concerns of censorship arise with this model, as previous models such as Stable Diffusion 2.0 were censored and were deemed of lower quality due to their anatomical distortions. It is hoped that SDXL 0.9 stays uncensored, as the community is ready to get working on it as soon as it hits public release.

Overall, the Stable Diffusion XL 0.9 update has several impressive features worth noting. Developers and users can expect to enjoy enhancements in depth of field, color gamut, and much more. Stable Diffusion XL 0.9 is set to be at the forefront of real-world applications for AI imagery, and we’re excited to see what the future holds for this powerful model. Although the image fidelity is not perfect yet, it is still an impressive achievement for a base model. As the open-source community is preparing to work on custom models, the future for SDXL art looks bright.

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