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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. This page lists notable large language models.
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. The largest and most capable LLMs are generative pretrained transformers (GPTs).
DBRX is an open-sourced large language model (LLM) developed by Mosaic ML team at Databricks, released on March 27, 2024. [1] [2] [3] It is a mixture-of-experts transformer model, with 132 billion parameters in total. 36 billion parameters (4 out of 16 experts) are active for each token. [4]
The DeepSeek-LLM series was released in November 2023. It has 7B and 67B parameters in both Base and Chat forms. DeepSeek's accompanying paper claimed benchmark results higher than Llama 2 and most open-source LLMs at the time. [29]: section 5 The model code is under the source-available DeepSeek License. [50]
It preserves BERT's architecture (slightly larger, at 355M parameters), but improves its training, changing key hyperparameters, removing the next-sentence prediction task, and using much larger mini-batch sizes. DistilBERT (2019) distills BERT BASE to a model with just 60% of its parameters (66M), while preserving 95% of its benchmark scores.
The Qwen-Vl series is a line of visual language models that combines a vision transformer with a LLM. [3] [13] Alibaba released Qwen-VL2 with variants of 2 billion and 7 billion parameters. [14] [15] Qwen-vl-max is Alibaba's flagship vision model as of 2024 and is sold by Alibaba Cloud at a cost of US$0.00041 per thousand input tokens. [16]
The papers most commonly cited as the originators that produced seq2seq are two concurrently published papers from 2014. [22] [23] A 380M-parameter model for machine translation uses two long short-term memories (LSTM). [23] Its architecture consists of two parts. The encoder is an LSTM that takes in a sequence of tokens and turns it into a vector.
Claude is a family of large language models developed by Anthropic. [1] [2] The first model was released in March 2023.The Claude 3 family, released in March 2024, consists of three models: Haiku, optimized for speed; Sonnet, which balances capability and performance; and Opus, designed for complex reasoning tasks.