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  2. Byte pair encoding - Wikipedia

    en.wikipedia.org/wiki/Byte_pair_encoding

    All the unique tokens found in a corpus are listed in a token vocabulary, the size of which, in the case of GPT-3.5 and GPT-4, is 100256. The modified tokenization algorithm initially treats the set of unique characters as 1-character-long n-grams (the initial tokens). Then, successively, the most frequent pair of adjacent tokens is merged into ...

  3. GPT-4 - Wikipedia

    en.wikipedia.org/wiki/GPT-4

    Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model trained and created by OpenAI and the fourth in its series of GPT foundation models. [1] It was launched on March 14, 2023, [1] and made publicly available via the paid chatbot product ChatGPT Plus, via OpenAI's API, and via the free chatbot Microsoft Copilot. [2]

  4. GPT-4o - Wikipedia

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

    It has a context length of 128k tokens [15] with an output token limit capped to 4,096, [16] and after a later update (gpt-4o-2024-08-06) to 16,384. [ 17 ] As of May 2024, it is the leading model in the LMSYS Elo Arena Benchmarks by the University of California, Berkeley .

  5. Universally unique identifier - Wikipedia

    en.wikipedia.org/wiki/Universally_unique_identifier

    As in other UUIDs, 4 bits are used to indicate version 4, and 2 or 3 bits to indicate the variant (10 2 or 110 2 for variants 1 and 2 respectively). Thus, for variant 1 (that is, most UUIDs) a random version 4 UUID will have 6 predetermined variant and version bits, leaving 122 bits for the randomly generated part, for a total of 2 122 , or 5.3 ...

  6. Transformer (deep learning architecture) - Wikipedia

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

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  7. Perplexity - Wikipedia

    en.wikipedia.org/wiki/Perplexity

    The simpler of these measures, WER, is simply the percentage of erroneously recognized words E (deletions, insertions, substitutions) to total number of words N, in a speech recognition task i.e. = % The second metric, perplexity (per token), is an information theoretic measure that evaluates the similarity of proposed model m to the original ...

  8. AutoGPT - Wikipedia

    en.wikipedia.org/wiki/AutoGPT

    Every step required in one of AutoGPT's tasks requires a corresponding call to GPT-4 at a cost of at least about $0.03 for every 1000 tokens used for inputs and $0.06 for every 1000 tokens for output when choosing the cheapest option. [14] For reference, 1000 tokens roughly result in 750 words. [14]

  9. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    ChatGPT is a generative artificial intelligence chatbot [2] [3] 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. [4]