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  2. DeepSeek - Wikipedia

    en.wikipedia.org/wiki/DeepSeek

    DeepSeek-V2 was released in May 2024. In June 2024, the DeepSeek-Coder V2 series was released. [32] The DeepSeek login page shortly after a cyberattack that occurred following its January 20 launch. DeepSeek V2.5 was released in September and updated in December 2024. [33] On 20 November 2024, DeepSeek-R1-Lite-Preview became accessible via API ...

  3. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    Hugging Face, Inc. is an American company incorporated under the Delaware General Corporation Law [1] and based in New York City that develops computation tools for building applications using machine learning.

  4. Reinforcement learning from human feedback - Wikipedia

    en.wikipedia.org/wiki/Reinforcement_learning...

    Human feedback is commonly collected by prompting humans to rank instances of the agent's behavior. [15] [17] [18] These rankings can then be used to score outputs, for example, using the Elo rating system, which is an algorithm for calculating the relative skill levels of players in a game based only on the outcome of each game. [3]

  5. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    GPT-2 deployment is resource-intensive; the full version of the model is larger than five gigabytes, making it difficult to embed locally into applications, and consumes large amounts of RAM. In addition, performing a single prediction "can occupy a CPU at 100% utilization for several minutes", and even with GPU processing, "a single prediction ...

  6. 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.

  7. Transformer (deep learning architecture) - Wikipedia

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

    The architecture of V2, showing both MLA and a variant of mixture of experts. [86]: Figure 2 Multihead Latent Attention (MLA) is a low-rank approximation to standard MHA. Specifically, each hidden vector, before entering the attention mechanism, is first projected to two low-dimensional spaces ("latent space"), one for query and one for key ...

  8. BERT (language model) - Wikipedia

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

    SQuAD (Stanford Question Answering Dataset [13]) v1.1 and v2.0; SWAG (Situations With Adversarial Generations [ 14 ] ). In the original paper, all parameters of BERT are finetuned, and recommended that, for downstream applications that are text classifications, the output token at the [CLS] input token is fed into a linear-softmax layer to ...

  9. deepset - Wikipedia

    en.wikipedia.org/wiki/Deepset

    deepset is an enterprise software vendor that provides developers with the tools to build production-ready natural language processing (NLP) systems. It was founded in 2018 in Berlin by Milos Rusic, Malte Pietsch, and Timo Möller.