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  2. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    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.

  3. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    ChatGPT is a generative artificial intelligence chatbot developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [2]

  4. Prompt injection - Wikipedia

    en.wikipedia.org/wiki/Prompt_injection

    Prompt injection is a cybersecurity exploit in which adversaries craft inputs that appear legitimate but are designed to cause unintended behavior in machine learning models, particularly large language models (LLMs). This attack takes advantage of the model's inability to distinguish between developer-defined prompts and user inputs, allowing ...

  5. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    The tendency towards larger models is visible in the list of large language models. As technology advanced, large sums have been invested in increasingly large models. For example, training of the GPT-2 (i.e. a 1.5-billion-parameters model) in 2019 cost $50,000, while training of the PaLM (i.e. a 540-billion-parameters model) in 2022 cost $8 ...

  6. GPT-4o - Wikipedia

    en.wikipedia.org/wiki/GPT-4o

    GPT-4o ("o" for "omni") is a multilingual, multimodal generative pre-trained transformer developed by OpenAI and released in May 2024. [1] GPT-4o is free, but ChatGPT Plus subscribers have higher usage limits. [2]

  7. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  8. Stellantis Opens Orders For Jailbreak Models As Part Of Dodge ...

    www.aol.com/news/stellantis-opens-orders...

    The Jailbreak model lets option combinations in more than 20 categories, including seven options for seats, stripes, and wheels; six brake caliper Stellantis Opens Orders For Jailbreak Models As ...

  9. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    In-context learning, refers to a model's ability to temporarily learn from prompts.For example, a prompt may include a few examples for a model to learn from, such as asking the model to complete "maison → house, chat → cat, chien →" (the expected response being dog), [23] an approach called few-shot learning.