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Introduction:
Personalized LLMs accelerator
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Prem provides a user-friendly platform for developing generative AI solutions, fine-tuning models, and retaining data sovereignty. Follow these steps: 1. Sign up on the website. 2. Choose between Developer or Business solutions. 3. Access open-source SLMs and custom models. 4. Collaborate with Prem for personalized AI strategies.

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35:23

Language Model Merging - Techniques, Tools, and Implementations

Model merging is an innovative approach in the field of language modeling that allows researchers and practitioners to combine multiple models into a single, more capable model without the need for additional training. This technique addresses the challenges of building high-performance models, which typically require significant time, resources, and computational power. Resources: Code: https://github.com/ALucek/language-model-merging Mergekit: https://github.com/arcee-ai/mergekit Julien Simon Model Merging Pt.1: https://youtu.be/cvOpX75Kz4M?si=Q91k0viO5e4seNRN Julien Simon Model Merging Pt.2: https://youtu.be/qbAvOgGmFuE?si=9DtMm3tEamjuX1kk Models Shown: Gemma w/Model Stock: https://huggingface.co/AdamLucek/gemma2-2b-it-chinese-german Llama w/SLERP: https://huggingface.co/AdamLucek/llama3-8b-code-sql-slerp Phi w/DELLA: https://huggingface.co/AdamLucek/Phi-3-mini-EmoMarketing-DELLA Mistral w/MoE: https://huggingface.co/AdamLucek/EduMixtral-4x7B Useful Blogs: Merging Models With Mergekit: https://huggingface.co/blog/mlabonne/merge-models Create a MoE: https://mlabonne.github.io/blog/posts/2024-03-28_Create_Mixture_of_Experts_with_MergeKit.html Model Merging: https://blog.premai.io/model-merging/ Papers: Model Soups: https://arxiv.org/pdf/2203.05482 SLERP: https://en.wikipedia.org/wiki/Slerp Task Arithmetic: https://arxiv.org/pdf/2212.04089 TIES: https://arxiv.org/pdf/2306.01708 DARE: https://arxiv.org/pdf/2311.03099 Model Breadcrumbs: https://arxiv.org/pdf/2312.06795 Model Stock: https://arxiv.org/pdf/2403.19522 DELLA: https://arxiv.org/pdf/2406.11617 Mixture of Experts: https://arxiv.org/pdf/2401.04088 Chapters: 00:00 - Intro 01:51 - Method: Linear (Model Soups) 03:14 - Method: SLERP (Spherical Interpolation) 05:14 - Method: Task Arithmetic 08:14 - Method: TIES (Trim & Elect Signs) 11:39 - Method: DARE (Drop & Rescale) 13:26 - Method: Model Breadcrumbs 15:09 - Method: Model Stock 16:58 - Method: DELLA (Drop & Rescale via Sampling with Magnitude) 18:33 - Method: Passthrough (Frankenmerging) 20:02 - Method: Mixture of Experts 21:57 - Merging Your Own Models 22:35 - Showcase: Gemma 2 2B w/Model Stock 23:39 - Showcase: Llama 3 8B w/Slerp 24:19 - Showcase: Phi 3 Mini w/DELLA 24:58 - Showcase: Mistral 7b w/Mixture of Experts 25:26 - How To: Understanding Mergekit 26:29 - How To: Picking Models & Method 27:03 - How To: Config File Setup 28:54 - How To: Merging the Models 31:32 - How To: Testing the Merged Model 34:36 - How To: Concluding Merging #ai #machinelearning #coding

Adam Lucek
Aug 12 2024
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Sep 26 2024
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