Скачать с ютуб Merge LLMs to Make Best Performing AI Model в хорошем качестве

Merge LLMs to Make Best Performing AI Model

This video is about mergekit, how to choose and blend models. It's non technical but links to technical papers are included. You need to know how to navigate the terminal but no programming is required. 🤖 Join my Discord community:   / discord   📰 My tutorials on Medium:   / mayaakim   🐦 My twitter profile:   / maya_akim   To rent a GPU from Massed Compute (mergekit preinstalled) follow the link ⤵️ https://bit.ly/maya-akim Code for 50% discount: MayaAkim All links: mergekit: https://github.com/arcee-ai/mergekit Open LLM Leaderboard https://huggingface.co/spaces/Hugging... my huggingface profile (with model configs you can copy): https://huggingface.co/mayacinka git installation: https://gitforwindows.org/ lfs installation: https://docs.github.com/en/repositori... supported architecture for mergekit: https://github.com/arcee-ai/mergekit/... best blog about mergekit:   / merge-large-language-models-with-mergekit   other really good blog about mergekit:   / merge-large-language-models   Charles Goddard’s blog: (author of mergekit) https://goddard.blog/about/ Mona lisa with Mohawk https://www.designboom.com/technology... What is YAML: https://www.techtarget.com/searchitop... What is Data Contamination: https://bdtechtalks.com/2023/07/17/ll... Goodharts law https://www.cna.org/reports/2022/09/g... LazyMergekit: https://colab.research.google.com/dri... Auto evaluation: (requires runpod profile) https://colab.research.google.com/dri... configuration with 14 models merged: https://huggingface.co/EmbeddedLLM/Mi... MoE instructions: https://github.com/arcee-ai/mergekit/... higher density - better results https://github.com/arcee-ai/mergekit/... Model family tree: (visualization) https://colab.research.google.com/dri... https://huggingface.co/spaces/mlabonn... cost of training mistral: https://www.ft.com/content/387eeeab-1... Leaderboard is disgusting:   / open_llm_leaderboard_is_disgusting   Merging models with different architectures: https://arxiv.org/pdf/2401.10491.pdf merging models different arch: https://github.com/18907305772/FuseLLM Blending is all you need: https://arxiv.org/pdf/2401.02994.pdf Model soups https://arxiv.org/pdf/2203.05482.pdf Ties-merging research paper: https://arxiv.org/pdf/2306.01708.pdf Dare merge research paper: https://arxiv.org/pdf/2311.03099.pdf Task arithemtic: https://arxiv.org/pdf/2212.04089.pdf Benchmarks Arc benchmarks https://deepgram.com/learn/arc-llm-be... https://arxiv.org/pdf/1803.05457.pdf HellaSwag https://arxiv.org/pdf/1905.07830.pdf MMLU https://arxiv.org/pdf/2009.03300.pdf TrithfulQA https://arxiv.org/abs/2109.07958 WinoGrande https://arxiv.org/pdf/1907.10641.pdf GSM8K https://arxiv.org/pdf/2110.14168.pdf overfitting problem Ann Lotz: https://arstechnica.com/tech-policy/2... Benchmarks are a problem screenshots: https://analyticsindiamag.com/the-pro...   / llm_benchmarks_are_broken_what_can_we_do_t...     / llm_benchmarks_are_bullshit   Attributions: [https://commons.wikimedia.org/wiki/Fi...](https://commons.wikimedia.org/wiki/Fi...) Timecodes: 0:00 - 1:47 - blending intro 1:48 - 3:36 - promise of blending 3:37 - 4:22 - blending steps and requirements 4:23 - 5:05 - all you need is hardware 5:06 - 5:30 - mergekit installation 5:31 - 9:23 - merge methods 10:48 - 13:31 - configurations and yaml 13:32 - 14:38 - how to run merge 14:39 - 14:42 - upload merged model 14:43 - 16:27 - best merge method 16:28 - 20:16 benchmark problems, overfitting and contamination #mergekit #llm #localmodels