Prompthero

Models by this creator

11.9K

openjourney

prompthero

openjourney is a Stable Diffusion model fine-tuned on Midjourney v4 images by the Replicate creator prompthero. It is similar to other Stable Diffusion models like stable-diffusion, stable-diffusion-inpainting, and the midjourney-style concept, which can produce images in a Midjourney-like style. Model inputs and outputs openjourney takes in a text prompt, an optional image, and various parameters like the image size, number of outputs, and more. It then generates one or more images that match the provided prompt. The outputs are high-quality, photorealistic images. Inputs Prompt**: The text prompt describing the desired image Image**: An optional image to use as guidance Width/Height**: The desired size of the output image Seed**: A random seed to control image generation Scheduler**: The algorithm used for image generation Guidance Scale**: The strength of the text guidance Negative Prompt**: Aspects to avoid in the output image Outputs Image(s)**: One or more generated images matching the input prompt Capabilities openjourney can generate a wide variety of photorealistic images from text prompts, with a focus on Midjourney-style aesthetics. It can handle prompts related to scenes, objects, characters, and more, and can produce highly detailed and imaginative outputs. What can I use it for? You can use openjourney to create unique, Midjourney-inspired artwork and illustrations for a variety of applications, such as: Generating concept art or character designs for games, films, or books Creating custom stock images or graphics for websites, social media, and marketing materials Exploring new ideas and visual concepts through freeform experimentation with prompts Things to try Some interesting things to try with openjourney include: Experimenting with different prompt styles and structures to see how they affect the output Combining openjourney with other Stable Diffusion-based models like qrcode-stable-diffusion or stable-diffusion-x4-upscaler to create unique visual effects Exploring the limits of the model's capabilities by pushing the boundaries of what can be generated with text prompts

Updated 12/13/2024

Text-to-Image

325

dreamshaper

prompthero

dreamshaper is a Stable Diffusion model created by PromptHero that aims to generate high-quality images from text prompts. It is designed to match the capabilities of models like Midjourney and DALL-E, and can produce a wide range of image types including photos, art, anime, and manga. dreamshaper has seen several iterations, with version 7 focusing on improving realism and NSFW handling compared to earlier versions. Model inputs and outputs dreamshaper takes in a text prompt describing the desired image, as well as optional parameters like seed, image size, number of outputs, and various scheduling options. The model then generates one or more images matching the input prompt. Inputs Prompt**: The text description of the desired image Seed**: A random seed value to control the image generation Width/Height**: The desired size of the output image (up to 1024x768 or 768x1024) Number of outputs**: The number of images to generate (up to 4) Scheduler**: The denoising scheduler to use Guidance scale**: The scale for classifier-free guidance Negative prompt**: Things to explicitly exclude from the output image Outputs Image(s)**: One or more generated images matching the input prompt Capabilities dreamshaper can generate a wide variety of photorealistic, artistic, and stylized images from text prompts. It is particularly adept at creating detailed portraits, intricate mechanical designs, and visually striking scenes. The model handles complex prompts well and is able to incorporate diverse elements like characters, environments, and abstract concepts. What can I use it for? dreamshaper can be a powerful tool for creative projects, visual storytelling, product design, and more. Artists and designers can use it to rapidly generate concepts and explore new ideas. Marketers and advertisers can leverage it to create eye-catching visuals for campaigns. Hobbyists can experiment with the model to bring their imaginative ideas to life. Things to try Try prompts that combine specific details with more abstract or imaginative elements, such as "a portrait of a muscular, bearded man in a worn mech suit, with elegant, vibrant colors and soft lighting." Explore the model's ability to handle different styles, genres, and visual motifs by experimenting with a variety of prompts.

Updated 12/13/2024

Text-to-Image

248

openjourney-v4

prompthero

openjourney-v4 is a Stable Diffusion 1.5 model fine-tuned by PromptHero on over 124,000 Midjourney v4 images. It is an extension of the openjourney model, which was also trained by PromptHero on Midjourney v4 images. The openjourney-v4 model aims to produce high-quality, Midjourney-style artwork from text prompts. Model inputs and outputs The openjourney-v4 model takes in a variety of inputs, including a text prompt, an optional starting image, image dimensions, and various other parameters to control the output image. The outputs are one or more images generated based on the provided inputs. Inputs Prompt**: The text prompt describing the desired image Image**: An optional starting image from which to generate variations Width/Height**: The desired dimensions of the output image Seed**: A random seed to control the image generation Scheduler**: The denoising scheduler to use Num Outputs**: The number of images to generate Guidance Scale**: The scale for classifier-free guidance Negative Prompt**: Text to avoid in the output image Prompt Strength**: The strength of the prompt when using an init image Num Inference Steps**: The number of denoising steps Outputs Image(s)**: One or more generated images, returned as a list of image URLs Capabilities The openjourney-v4 model can generate a wide variety of Midjourney-style images from text prompts, ranging from fantastical landscapes and creatures to realistic portraits and scenes. The model is particularly skilled at producing detailed, imaginative artwork with a distinct visual style. What can I use it for? The openjourney-v4 model can be used for a variety of creative and artistic applications, such as conceptual art, game asset creation, and illustration. It could also be used to quickly generate ideas or concepts for creative projects. The model's ability to produce high-quality, visually striking images makes it a valuable tool for designers, artists, and content creators. Things to try Experiment with different types of prompts, from specific and descriptive to more open-ended and abstract. Try combining the openjourney-v4 model with other Stable Diffusion-based models, such as openjourney-lora or dreamshaper, to see how the results can be further refined or enhanced.

Updated 12/13/2024

Text-to-Image

194

lookbook

prompthero

lookbook is a fashion-focused AI model developed by PromptHero. It is capable of generating high-quality images of people wearing various clothing items based on text prompts. This model is similar to PromptHero's openjourney, which has been fine-tuned on Midjourney v4 images, and oot_diffusion, a virtual dressing room model. lookbook can be used to explore fashion ideas, test clothing combinations, and experiment with different styles. Model inputs and outputs lookbook takes in a text prompt describing the desired clothing and image characteristics, and outputs one or more corresponding images. The input parameters include the prompt, image size, number of outputs, and other settings to control the generation process. Inputs Prompt**: The text prompt describing the desired clothing and image characteristics Seed**: A random seed value to control the generation process (optional) Width/Height**: The desired output image size, with a default of 512x512 Num Outputs**: The number of images to generate, with a default of 1 Scheduler**: The diffusion scheduler algorithm to use, with a default of "EULERa" Guidance Scale**: The strength of the guidance signal, with a default of 7 Num Inference Steps**: The number of denoising steps, with a default of 150 Outputs Output Images**: The generated images matching the input prompt Capabilities lookbook can create realistic and visually appealing images of people wearing a wide variety of clothing styles and fashion items. The model has been trained on a large dataset of fashion-related images, allowing it to capture the nuances of different fabrics, patterns, and silhouettes. By adjusting the input prompt, users can experiment with different outfits, accessories, and even moods or settings. What can I use it for? lookbook can be a valuable tool for fashion designers, stylists, and enthusiasts. It can be used to visualize new clothing designs, experiment with different outfit combinations, or create mood boards for fashion-related projects. Additionally, the model can be used to generate images for marketing, e-commerce, or social media purposes, helping to showcase products or inspire customers. Things to try With lookbook, you can explore a wide range of fashion-related prompts, from classic outfits to more avant-garde designs. Try experimenting with different clothing items, accessories, and even styling cues to see how the model responds. You can also play with the input parameters, such as the guidance scale and number of inference steps, to fine-tune the generated images to your liking.

Updated 12/13/2024

Text-to-Image

🔍

156

openjourney-lora

prompthero

The openjourney-lora model is a LoRA (Low-Rank Adaptation) adaptation of the Openjourney AI model, created by PromptHero. LoRA is a technique for fine-tuning large language models on specific tasks while preserving the original model's weights. This enables the model to be efficiently adapted for various use cases. The Openjourney model is a text-to-image AI that can generate highly detailed and imaginative artwork based on text prompts. The openjourney-lora model builds upon this foundation, offering additional capabilities and fine-tuned performance. Model inputs and outputs Inputs Text prompts describing the desired image Outputs Generated images based on the input text prompts Capabilities The openjourney-lora model is capable of generating a wide range of artistic and imaginative images. It can produce detailed portraits, fantastical landscapes, and surreal scenes. The model excels at capturing various artistic styles and mediums, from photorealistic to impressionistic. What can I use it for? The openjourney-lora model can be used for a variety of creative and artistic applications. It can be leveraged by artists, designers, and content creators to generate unique visual assets for their projects, such as illustrations, concept art, and cover images. Additionally, the model can be used for personal creative expression, allowing users to bring their imaginations to life through text-based image generation. Things to try One interesting aspect of the openjourney-lora model is its ability to generate images with a high level of detail and complexity. Users can experiment with detailed prompts that incorporate specific artistic elements, such as unique lighting, textures, or color palettes, to see how the model responds and adapts. Additionally, users can explore the model's versatility by trying different prompt styles, from descriptive narratives to more abstract, conceptual prompts, to uncover the breadth of its creative potential.

Updated 5/27/2024

Text-to-Image

epicrealism

prompthero

epicrealism is a text-to-image generation model developed by prompthero. It is capable of generating new images based on any input text prompt. epicrealism can be compared to similar models like Dreamshaper, Stable Diffusion, Edge of Realism v2.0, and GFPGAN, all of which can generate images from text prompts. Model inputs and outputs epicrealism takes a text prompt as input and generates one or more images as output. The model also allows for additional parameters like seed, image size, scheduler, number of outputs, guidance scale, negative prompt, prompt strength, and number of inference steps. Inputs Prompt**: The text prompt that describes the image to be generated Seed**: A random seed value to control the randomness of the generated image Width**: The width of the output image Height**: The height of the output image Scheduler**: The algorithm used for image generation Num Outputs**: The number of images to generate Guidance Scale**: The scale for classifier-free guidance Negative Prompt**: Text describing things to not include in the output image Prompt Strength**: The strength of the prompt when using an initial image Num Inference Steps**: The number of denoising steps during image generation Outputs Image**: One or more images generated based on the input prompt and parameters Capabilities epicrealism can generate a wide variety of photorealistic images based on text prompts, from landscapes and scenes to portraits and abstract art. It is particularly adept at creating images with a high level of detail and realism, making it a powerful tool for creative applications. What can I use it for? You can use epicrealism to create unique and visually striking images for a variety of purposes, such as art projects, product design, advertising, and more. The model's ability to generate images from text prompts makes it a versatile tool for anyone looking to bring their creative ideas to life. Things to try One interesting aspect of epicrealism is its ability to generate images with a strong sense of realism and detail. You could try experimenting with detailed prompts that describe specific scenes, objects, or characters, and see how the model renders them. Additionally, you could explore the use of negative prompts to refine the output and exclude certain elements from the generated images.

Updated 12/13/2024

Text-to-Image

majicmix

prompthero

majicMix is an AI model developed by prompthero that can generate new images from text prompts. It is similar to other text-to-image models like Stable Diffusion, DreamShaper, and epiCRealism. These models all use diffusion techniques to transform text inputs into photorealistic images. Model inputs and outputs The majicMix model takes several inputs to generate the output image, including a text prompt, a seed value, image dimensions, and various settings for the diffusion process. The outputs are one or more images that match the input prompt. Inputs Prompt**: The text description of the desired image Seed**: A random number that controls the image generation process Width & Height**: The size of the output image Scheduler**: The algorithm used for the diffusion process Num Outputs**: The number of images to generate Guidance Scale**: The strength of the text guidance during generation Negative Prompt**: Text describing things to avoid in the output Prompt Strength**: The balance between the input image and the text prompt Num Inference Steps**: The number of denoising steps in the diffusion process Outputs Image**: One or more generated images matching the input prompt Capabilities majicMix can generate a wide variety of photorealistic images from text prompts, including scenes, portraits, and abstract concepts. The model is particularly adept at creating highly detailed and imaginative images that capture the essence of the prompt. What can I use it for? majicMix could be used for a variety of creative applications, such as generating concept art, illustrations, or stock images. It could also be used in marketing and advertising to create unique and eye-catching visuals. Additionally, the model could be leveraged for educational or scientific purposes, such as visualizing complex ideas or data. Things to try One interesting aspect of majicMix is its ability to generate images with a high level of realism and detail. Try experimenting with specific, detailed prompts to see the level of fidelity the model can achieve. Additionally, you could explore the model's capabilities for more abstract or surreal image generation by using prompts that challenge the boundaries of reality.

Updated 12/13/2024

Text-to-Image

funko-diffusion

prompthero

funko-diffusion is a Stable Diffusion model fine-tuned by prompthero on Funko Pop images. This model builds on the capabilities of the original Stable Diffusion model, which is a powerful text-to-image diffusion model capable of generating highly detailed and realistic images from text prompts. The funko-diffusion model has been further trained on a dataset of Funko Pop figurines, allowing it to generate images that capture the unique style and aesthetic of these popular collectibles. Model inputs and outputs The funko-diffusion model takes a text prompt as input and generates one or more images as output. The input prompt can describe the desired Funko Pop figure, including its character, design, and other details. The model then uses this prompt to create a corresponding image that matches the specified characteristics. Inputs Prompt**: The text prompt describing the desired Funko Pop figure Seed**: A random seed value to control the image generation process Width/Height**: The desired dimensions of the output image Number of outputs**: The number of images to generate Guidance scale**: A parameter that controls the balance between the text prompt and the model's internal knowledge Number of inference steps**: The number of denoising steps to perform during image generation Outputs Image(s)**: One or more generated images that match the input prompt Capabilities The funko-diffusion model is capable of generating highly detailed and accurate Funko Pop-style images from text prompts. It can capture the distinct visual characteristics of Funko Pop figures, such as their large heads, expressive faces, and simplified body shapes. The model can also incorporate specific details about the character, such as their outfit, accessories, and pose. What can I use it for? The funko-diffusion model can be used for a variety of applications, such as: Creating custom Funko Pop-inspired artwork and merchandise Visualizing ideas for new Funko Pop designs Generating images for use in marketing, advertising, or social media Experimenting with different Funko Pop character concepts and designs Things to try Some ideas for experimenting with the funko-diffusion model include: Trying different prompts to see how the model handles various Funko Pop character types and designs Adjusting the model parameters, such as the guidance scale and number of inference steps, to explore the range of generated images Combining the funko-diffusion model with other AI-powered tools, such as stable-diffusion-inpainting, to create more complex and personalized Funko Pop artworks Exploring the model's capabilities for generating Funko Pop-inspired scenes or dioramas by including additional elements in the prompt

Updated 12/13/2024

Text-to-Image

poolsuite-diffusion

prompthero

The poolsuite-diffusion model is a fine-tuned Dreambooth model that aims to reproduce the "Poolsuite" aesthetic. Dreambooth is a technique for training custom Stable Diffusion models on a small set of images, similar to dreambooth and analog-diffusion. The model was created by prompthero. Model inputs and outputs The poolsuite-diffusion model takes a text prompt as input and generates one or more images that match the provided prompt. The key inputs are: Inputs Prompt**: The text prompt describing the desired image Width/Height**: The desired dimensions of the output image Seed**: A random seed to control image generation (leave blank to randomize) Num Outputs**: The number of images to generate Guidance Scale**: The degree of influence the text prompt has on the generated image Num Inference Steps**: The number of denoising steps to take during generation Outputs Output Images**: One or more images generated based on the provided inputs Capabilities The poolsuite-diffusion model can generate images with a distinct "Poolsuite" visual style, which is characterized by vibrant colors, retro aesthetics, and a relaxed, summery vibe. The model is especially adept at producing images of vintage cars, landscapes, and poolside scenes that capture this specific aesthetic. What can I use it for? You can use the poolsuite-diffusion model to generate images for a variety of creative projects, such as album covers, social media content, or marketing materials with a distinctive retro-inspired look and feel. The model's ability to capture the "Poolsuite" aesthetic makes it well-suited for projects that aim to evoke a sense of nostalgia or relaxation. Things to try Try experimenting with different prompts that incorporate keywords or concepts related to vintage cars, California landscapes, or poolside settings. You can also play with the various input parameters, such as the guidance scale and number of inference steps, to see how they affect the final output and the degree of "Poolsuite" fidelity.

Updated 12/13/2024

Text-to-Image