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  2. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  3. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.

  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. HHL Leipzig Graduate School of Management - Wikipedia

    en.wikipedia.org/wiki/HHL_Leipzig_Graduate...

    The Leipzig Leadership Model (LLM) is an interdisciplinary and multidimensional framework for good leadership developed at HHL Leipzig Graduate School of Management in 2016. [20] The LLM uses its four dimensions (purpose, entrepreneurial spirit, effectiveness and responsibility) to link important questions of meaning and values with the ...

  6. Llama (language model) - Wikipedia

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

    Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024.

  7. BERT (language model) - Wikipedia

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

    High-level schematic diagram of BERT. It takes in a text, tokenizes it into a sequence of tokens, add in optional special tokens, and apply a Transformer encoder. The hidden states of the last layer can then be used as contextual word embeddings. BERT is an "encoder-only" transformer architecture. At a high level, BERT consists of 4 modules:

  8. 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).

  9. PaLM - Wikipedia

    en.wikipedia.org/wiki/PaLM

    PaLM (Pathways Language Model) is a 540 billion-parameter dense decoder-only transformer-based large language model (LLM) developed by Google AI. [1] Researchers also trained smaller versions of PaLM (with 8 and 62 billion parameters) to test the effects of model scale.