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  2. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    The Reflexion method [68] constructs an agent that learns over multiple episodes. At the end of each episode, the LLM is given the record of the episode, and prompted to think up "lessons learned", which would help it perform better at a subsequent episode. These "lessons learned" are given to the agent in the subsequent episodes. [citation needed]

  3. BLOOM (language model) - Wikipedia

    en.wikipedia.org/wiki/BLOOM_(language_model)

    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]

  4. Mamba (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Mamba_(deep_learning...

    Mamba LLM represents a significant potential shift in large language model architecture, offering faster, more efficient, and scalable models [citation needed]. Applications include language translation, content generation, long-form text analysis, audio, and speech processing [citation needed

  5. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    If they used 20 to make lunch and bought 6 more, how many apples do they have?", Google claims that a CoT prompt might induce the LLM to answer "A: The cafeteria had 23 apples originally. They used 20 to make lunch. So they had 23 - 20 = 3. They bought 6 more apples, so they have 3 + 6 = 9. The answer is 9."

  6. Llama (language model) - Wikipedia

    en.wikipedia.org/wiki/Llama_(language_model)

    The model was exclusively a foundation model, [6] although the paper contained examples of instruction fine-tuned versions of the model. [ 2 ] Meta AI reported the 13B parameter model performance on most NLP benchmarks exceeded that of the much larger GPT-3 (with 175B parameters), and the largest 65B model was competitive with state of the art ...

  7. Gemini (language model) - Wikipedia

    en.wikipedia.org/wiki/Gemini_(language_model)

    Gemini's launch was preluded by months of intense speculation and anticipation, which MIT Technology Review described as "peak AI hype". [50] [20] In August 2023, Dylan Patel and Daniel Nishball of research firm SemiAnalysis penned a blog post declaring that the release of Gemini would "eat the world" and outclass GPT-4, prompting OpenAI CEO Sam Altman to ridicule the duo on X (formerly Twitter).