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At the time of the MMLU's release, most existing language models performed around the level of random chance (25%), with the best performing GPT-3 model achieving 43.9% accuracy. [3] The developers of the MMLU estimate that human domain-experts achieve around 89.8% accuracy. [ 3 ]
He has used Codeforces problems in his class, 15-295: Competition Programming and Problem Solving. [20] At the National University of Singapore , Codeforces rating is also used as an entrance qualifying criterion for registering for a 4-unit course, CS3233 Competitive Programming, as students have to achieve a rating of at least 1559 to be able ...
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. [28]: section 5 The model code is under the source-available DeepSeek License. [49]
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]
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]
When a programmer submits a solution to a programming challenge, their submission is scored on the accuracy of their output. Programmers are then ranked globally on the HackerRank leaderboard and earn badges based on their accomplishments, which is intended to drive competition among users.
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.
Code Llama is a fine-tune of LLaMa 2 with code specific datasets. 7B, 13B, and 34B versions were released on August 24, 2023, with the 70B releasing on the January 29, 2024. [29] Starting with the foundation models from LLaMa 2, Meta AI would train an additional 500B tokens of code datasets, before an additional 20B token of long-context data ...