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text2image-prompt-generator

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text2image-prompt-generator is a GPT-2 model fine-tuned on a dataset of 250,000 text prompts used by users of the Midjourney text-to-image service. This prompt generator can be used to auto-complete prompts for any text-to-image model, including the DALL-E family. While the model can be used with any text-to-image system, it may occasionally produce Midjourney-specific tags. Users can specify requirements via parameters or set the importance of various entities in the image. Similar models include Fast GPT2 PromptGen, Fast Anime PromptGen, and SuperPrompt, all of which focus on generating high-quality prompts for text-to-image models. Model Inputs and Outputs Inputs Free-form text prompt to be used as a starting point for generating an expanded, more detailed prompt Outputs Expanded, detailed text prompt that can be used as input for a text-to-image model like Midjourney, DALL-E, or Stable Diffusion Capabilities The text2image-prompt-generator model can take a simple prompt like "a cat sitting" and expand it into a more detailed, nuanced prompt such as "a tabby cat sitting on a windowsill, gazing out at a cityscape with skyscrapers in the background, sunlight streaming in through the window, the cat's eyes alert and focused". This can help generate more visually interesting and detailed images from text-to-image models. What Can I Use It For? The text2image-prompt-generator model can be used to quickly and easily generate more expressive prompts for any text-to-image AI system. This can be particularly useful for artists, designers, or anyone looking to create compelling visual content from text. By leveraging the model's ability to expand and refine prompts, you can explore more creative directions and potentially produce higher quality images. Things to Try While the text2image-prompt-generator model is designed to work with a wide range of text-to-image systems, you may find that certain parameters or techniques work better with specific models. Experiment with using the model's output as a starting point, then further refine the prompt with additional details, modifiers, or Midjourney parameters to get the exact result you're looking for. You can also try using the model's output as a jumping-off point for contrastive search to generate a diverse set of prompts.

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