Yi Cui's picture

Yi Cui

onekq

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https://onekq.ai

AI & ML interests

Benchmark, Code Generation Model

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posted an update 1 day ago

This post discussed the same trend as the Sutton post, but is more concrete and down-to-earth. https://ysymyth.github.io/The-Second-Half/ Two takeaways for me. (1) deep neural network is the backbone to unify everything. RLHF will stand the test of time because it brings two distinct fields (NLP and RL) onto the same model weights. (2) language model will continue to play a central role in the era of agent. It probably won't be the end game to AGI, but definitely not offramp.

reacted to JLouisBiz's post with 🔥 1 day ago

Back to LLM integration. ClickDefine.sh -- quickly define or explain anything within your whole desktop environment You only need to run the model locally, maybe with the **llama.cpp** or **ollama** - https://github.com/ggml-org/llama.cpp - https://ollama.com/download And you get universal explaining tool that works anywhere on your X Org Desktop (on operating systems which are usually Fully Free Software like Debian GNU/Linux) ClickDefine - Interactive Text Processor Script for Iterative LLM Query Handling: https://hyperscope.link/9/6/0/9/8/ClickDefine-Interactive-Text-Processor-Script-for-Iterative-LLM-Query-Handling-96098.html Watch the demonstration here: https://www.youtube.com/watch?v=mQxCYAiReu0&t=2s

posted an update 3 days ago

This is bitter lesson 2.0 https://storage.googleapis.com/deepmind-media/Era-of-Experience%20/The%20Era%20of%20Experience%20Paper.pdf If this reads too lofty to you, consider some low-hanging fruits. Experiences here are reward signals we send to LLMs, e.g. human score in RLHF, verification in AlphaProof, or test results for code generation. RFT (reinforced finetuning) will become main stream, and IMO make LLMs behave more like agents.

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liked a Space 6 months ago

Quant Request

Submit Hugging Face model links for quantization requests