Summary of Reactor Mk.1 Performances: Mmlu, Humaneval and Bbh Test Results, by Tj Dunham et al.
Reactor Mk.1 performances: MMLU, HumanEval and BBH test results
by TJ Dunham, Henry Syahputra
First submitted to arxiv on: 15 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A new large language model, Reactor Mk.1, has been benchmarked using various datasets to evaluate its performance. This model, powered by the Lychee AI engine, boasts fewer than 100 billion parameters, allowing for a balance between efficiency and capability. Compared to other models like GPT-4o, Claude Opus, and Llama 3, Reactor Mk.1 achieved scores of 92% on MMLU, 91% on HumanEval, and 88% on BBH datasets. The model’s strengths lie in its ability to handle complex tasks and reason effectively, solidifying its position as a leading AI solution in the current cutting-edge AI landscape. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Reactor Mk.1 is a new large language model that uses the Lychee AI engine. It has fewer than 100 billion parameters, which makes it efficient and good at doing things. The model was tested on different datasets and did well compared to other models like GPT-4o, Claude Opus, and Llama 3. Reactor Mk.1 scored 92% on the MMLU dataset, 91% on the HumanEval dataset, and 88% on the BBH dataset. The model is good at doing difficult tasks and thinking logically, making it a leading AI solution. |
Keywords
» Artificial intelligence » Claude » Gpt » Large language model » Llama
