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Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.
These models take text prompts as input and use them to generate AI-generated images. Text-to-image models typically do not understand grammar and sentence structure in the same way as large language models, [49] thus may require a different set of prompting techniques. Text-to-image models do not natively understand negation.
Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [128] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [129] and reweighting training data. [130]
By adjusting the "image weight" parameter, users can prioritize either the content of the prompt or the characteristics of the image. For instance, setting a higher weight will ensure that the generated result closely follows the image's structure and details, while a lower weight allows the text prompt to have more influence over the final output.
The Stable Diffusion model supports the ability to generate new images from scratch through the use of a text prompt describing elements to be included or omitted from the output. [8] Existing images can be re-drawn by the model to incorporate new elements described by a text prompt (a process known as "guided image synthesis" [ 49 ] ) through ...
GPT-2 can generate thematically-appropriate text for a range of scenarios, even surreal ones like a CNN article about Donald Trump giving a speech praising the anime character Asuka Langley Soryu. Here, the tendency to generate nonsensical and repetitive text with increasing output length (even in the full 1.5B model) can be seen; in the second ...
DALL-E, DALL-E 2, and DALL-E 3 (stylised DALL·E, and pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.
GPT-J was designed to generate English text from a prompt. It was not designed for translating or generating text in other languages or for performance without first fine-tuning the model for a specific task. [2] Nonetheless, GPT-J performs reasonably well even without fine-tuning, even in translation (at least from English to French). [8]