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  2. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    The company was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf in New York City, originally as a company that developed a chatbot app targeted at teenagers. [1] The company was named after the U+1F917 珞 HUGGING FACE emoji. [1]

  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. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    Since the transformer architecture enabled massive parallelization, GPT models could be trained on larger corpora than previous NLP (natural language processing) models.. While the GPT-1 model demonstrated that the approach was viable, GPT-2 would further explore the emergent properties of networks trained on extremely large corpo

  5. GPT-4o - Wikipedia

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

    According to OpenAI, its low cost is expected to be particularly useful for companies, startups, and developers that seek to integrate it into their services, which often make a high number of API calls. Its API costs $0.15 per million input tokens and $0.6 per million output tokens, compared to $5 and $15, respectively, for GPT-4o.

  6. 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 ...

  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).

  8. 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]

  9. Llama (language model) - Wikipedia

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

    key hyperparameters of Llama 3.1 8B 70B 405B Layers 32 80 126 Model Dimension 4,096 8,192 16,384 FFN Dimension 14,336 28,672 53,248 Attention Heads 32 64 128 Key/Value Heads 8 8 8 Peak Learning Rate 3 × 10 −4: 1.5 × 10 −4: 0.8 × 10 −4: Activation Function SwiGLU Vocabulary Size 128,000 Positional Embeddings