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LLMS
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Frontier Models Creation at Fractional Compute Budget
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Recipe to create frontier models at fractional compute budget!
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Best Practitioners Fine-Tune AI Models on PDF Documents
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This is also my experience. The best of the best are the people who want to fine-tune on PDFs.
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MIT Professors Explore Generative AI Potential Language Code Images
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MIT professors on the expansive potential of generative AI, including language, code, & images: https://t.co/Pq0HG2B0Uc pic.twitter.com/5DDiMl9MFB
— MIT CSAIL (@MIT_CSAIL) 21 novembre 2024MIT professors on the expansive potential of generative AI, including language, code, & images: https://
bit.ly/3Z1eqmV -
Key Metrics and Evaluation Methods for RAG Systems
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New video! Key Metrics and Evaluation Methods for RAG Learn more: https://
youtu.be/cRz0BWkuwHg #llms #rag #evaluation -
Prometheus 2 Model Merging with LazyMergekit Technique
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True, this is even older than this paper. Several authors pinged me about it like Prometheus 2 (they used LazyMergekit haha): https://
arxiv.org/abs/2405.01535 -
New leaderboard ranks LLMs for LLM-as-a-judge; Llama-3.1-70B tops
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New leaderboard ranks LLMs for LLM-as-a-judge: Llama-3.1-70B tops the rankings! Evaluating systems is critical during prototyping and in production, and LLM-as-a-judge has become a standard technique to do it. First, what is "LLM-as-a-judge"? It's a very useful technique
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Fine-tuning Llama 3 8B Outperforms GPT-4o for Specialized Tasks
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Fine-tuning #OpenSource models like Llama 3 8B can outperform GPT-4o for specialized tasks, providing results that are … faster cheaper and more accurate Read more https://
sambanova.ai/blog/outperfor
ming-gpt-4o-with-llama-3-8b-fine-tuning-rag
… #RAG #GPT -
Text Content Optimized for LLM Consumption Emerging Online
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A small number of people are posting text online that’s intended for direct consumption not by humans, but by LLMs (large language models). I find this a fascinating trend, particularly when writers are incentivized to help LLM providers better serve their users! People who post
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Merging Smol-Talk and Orca-AgentInstruct Models
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Secondary question: what if you merge the model trained on Smol-Talk and the one trained on Orca-AgentInstruct-1M?