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🔄 In a Training Loop

Tarun Jain

lucifertrj
11 7 15
Gargaz's profile picture tegridydev's profile picture arunrajuamrutha's profile picture
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https://youtube.com/@aiwithtarun

AI & ML interests

Deep Learning, FPGA, and ML

Recent Activity

repliedto their post 3 days ago
You can now automate EDD (eval-driven development) with Coding Harness Agents > build a baseline LLM-based application > score every change with judge evals > keep what improves, reject what regresses I made a tutorial on what EDD is, how it works, and how to use eval scores across experiments to improve an LLM app. It builds on Jeffrey's (Confident AI) article on EDD and Eugene Yan's write-up on product evals. > Setup: a baseline RAG app using Qdrant and Gemini that every experiment starts from > Step 1: a binary-labelled dataset with critiques > Step 2: aligning the LLM-as-a-judge evaluator with Opik evals > Step 3: a harness loop that runs each experiment and scores it against the baseline. Tracing and experiment comparison then show what improved, what regressed, and what to tweak next. Source code is open source. Full guide (source code linked in the description): https://www.youtube.com/watch?v=e6akw_fKWPk
liked a model 4 days ago
kaividlabs/LFM2.5-2.6B-litertlm
updated a model 4 days ago
kaividlabs/LFM2.5-2.6B-litertlm
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