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Jan Jakubcik

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reacted to danielhanchen's post with ❤️ about 24 hours ago

We created a tool-calling guide for local LLMs! Learn how to use any open model like Qwen3-Coder-Next and GLM-4.7-Flash for function calling. Guide: https://unsloth.ai/docs/basics/tool-calling-guide-for-local-llms We provide hands-on examples for: story writing, Python execution, terminal tool calls, maths and more.

reacted to codelion's post with 🔥 6 months ago

Implemented Test-Time Diffusion Deep Researcher (TTD-DR) in OptiLLM! 🚀 Just shipped a game-changing feature that turns any LLM into a powerful research agent. TTD-DR applies diffusion-inspired techniques to iteratively refine research reports while grounding them in real web sources. How it works: • Generates initial draft • Identifies knowledge gaps • Searches web for missing info • Iteratively refines through "denoising" steps • Produces comprehensive reports with 15-30+ sources The magic? It works with ANY model so you can choose your favorite open-source models on HF! Key results: - 47 complex research queries tested - Every report backed by real web sources - Quality rivals human research analysts - No more hallucinations on current events! Try it: pip install optillm Then use "deep_research-your-model-name" as the model identifier - Implementation: https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research - Paper: https://arxiv.org/abs/2507.16075v1 - Sample reports: https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research/sample_reports Special thanks to the TTD-DR paper authors for this brilliant approach! #research #llm #opensource #inference

new activity 11 months ago

agents-course/unit2_smolagents_quiz:I finish the test and click submit but i dont get notified about a new certificate

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