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  2. Llama (language model) - Wikipedia

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

    Prompt: A representation of Meta AI and Llama On April 18, 2024, Meta released Llama-3 with two sizes: 8B and 70B parameters. [ 18 ] The models have been pre-trained on approximately 15 trillion tokens of text gathered from “publicly available sources” with the instruct models fine-tuned on “publicly available instruction datasets, as ...

  3. llama.cpp - Wikipedia

    en.wikipedia.org/wiki/Llama.cpp

    llama.cpp is an open source software library that performs inference on various large language models such as Llama. [3] It is co-developed alongside the GGML project, a general-purpose tensor library.

  4. Response-prompting procedures - Wikipedia

    en.wikipedia.org/wiki/Response-prompting_procedures

    The SLP prompting procedure uses and removes prompts by moving through a hierarchy from less to more restrictive prompts. [2] [3] [4] If the student emits the correct behavior at any point during this instructional trial [5] (with or without prompts), reinforcement is provided. The system of least prompts gives the learner the opportunity to ...

  5. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Prompt engineering is the process of structuring or crafting an instruction in order to produce the best possible output from a generative artificial intelligence ...

  6. 8b/10b encoding - Wikipedia

    en.wikipedia.org/wiki/8b/10b_encoding

    An 8b/10b code can be implemented in various ways with focus on different performance parameters. One implementation was designed by K. Odaka for the DAT digital audio recorder. [2] Kees Schouhamer Immink designed an 8b/10b code for the DCC audio recorder. [3] The IBM implementation was described in 1983 by Al Widmer and Peter Franaszek. [4] [5]

  7. Backward chaining - Wikipedia

    en.wikipedia.org/wiki/Backward_chaining

    Backward chaining (or backward reasoning) is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers, inference engines, proof assistants, and other artificial intelligence applications.

  8. Testing effect - Wikipedia

    en.wikipedia.org/wiki/Testing_effect

    When compared to concept mapping alone, retrieval practice is more beneficial, [104] despite students not seeing retrieval practice as a useful learning tool. [105] When combined, learner performance was increased, suggesting concept mapping is a tool that should be combined with retrieval practice [ 106 ] alongside other non-verbal responses ...

  9. Mastery learning - Wikipedia

    en.wikipedia.org/wiki/Mastery_learning

    The motivation for mastery learning comes from trying to reduce achievement gaps for students in average school classrooms. During the 1960s John B. Carroll and Benjamin S. Bloom pointed out that, if students are normally distributed with respect to aptitude for a subject and if they are provided uniform instruction (in terms of quality and learning time), then achievement level at completion ...