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Mert Erbak PRO

merterbak

AI & ML interests

NLP and Image Processing

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merterbak's activity

reacted to their post with πŸ”₯❀️ about 22 hours ago
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3363
FlowReasoner is a new system that builds a custom set of small AI agents for every user question. Unlike search based methods it uses reasoning driven optimization with external execution feedback.

βœ… First, it distills reasoning data using DeepSeek R1-671B to build multi agent systems. πŸ€–
βœ… Then, reasoning data used for DeepSeek-R1-Distill-Qwen-7B via supervised fine tuning for basic reasoning skills. πŸ’‘
βœ… Finally, RL with GRPO (optimizes by comparing response groups from queries/tasks) to improve reasoning.

FlowReasoner: Reinforcing Query-Level Meta-Agents (2504.15257)
Code: https://github.com/sail-sg/flowreasoner
reacted to julien-c's post with πŸ”₯ 3 days ago
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3431
BOOOOM: Today I'm dropping TINY AGENTS

the 50 lines of code Agent in Javascript πŸ”₯

I spent the last few weeks working on this, so I hope you will like it.

I've been diving into MCP (Model Context Protocol) to understand what the hype was all about.

It is fairly simple, but still quite powerful: MCP is a standard API to expose sets of Tools that can be hooked to LLMs.

But while doing that, came my second realization:

Once you have a MCP Client, an Agent is literally just a while loop on top of it. 🀯

➑️ read it exclusively on the official HF blog: https://huggingface.co/blog/tiny-agents
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reacted to their post with πŸš€ 3 days ago
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3363
FlowReasoner is a new system that builds a custom set of small AI agents for every user question. Unlike search based methods it uses reasoning driven optimization with external execution feedback.

βœ… First, it distills reasoning data using DeepSeek R1-671B to build multi agent systems. πŸ€–
βœ… Then, reasoning data used for DeepSeek-R1-Distill-Qwen-7B via supervised fine tuning for basic reasoning skills. πŸ’‘
βœ… Finally, RL with GRPO (optimizes by comparing response groups from queries/tasks) to improve reasoning.

FlowReasoner: Reinforcing Query-Level Meta-Agents (2504.15257)
Code: https://github.com/sail-sg/flowreasoner
posted an update 3 days ago
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3363
FlowReasoner is a new system that builds a custom set of small AI agents for every user question. Unlike search based methods it uses reasoning driven optimization with external execution feedback.

βœ… First, it distills reasoning data using DeepSeek R1-671B to build multi agent systems. πŸ€–
βœ… Then, reasoning data used for DeepSeek-R1-Distill-Qwen-7B via supervised fine tuning for basic reasoning skills. πŸ’‘
βœ… Finally, RL with GRPO (optimizes by comparing response groups from queries/tasks) to improve reasoning.

FlowReasoner: Reinforcing Query-Level Meta-Agents (2504.15257)
Code: https://github.com/sail-sg/flowreasoner
reacted to fdaudens's post with πŸ”₯ 4 days ago
reacted to meg's post with πŸ”₯ 5 days ago
reacted to clem's post with πŸ”₯ 5 days ago
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3763
Energy is a massive constraint for AI but do you even know what energy your chatGPT convos are using?

We're trying to change this by releasing ChatUI-energy, the first interface where you see in real-time what energy your AI conversations consume. Great work from @jdelavande powered by spaces & TGI, available for a dozen of open-source models like Llama, Mistral, Qwen, Gemma and more.

jdelavande/chat-ui-energy

Should all chat interfaces have this? Just like ingredients have to be shown on products you buy, we need more transparency in AI for users!
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