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Isaac Kargar

kargarisaac

https://kargarisaac.github.io/blog/

AI & ML interests

Interested in computer vision, nlp, and reinforcement learning

Recent Activity

upvoted an article 14 days ago

Open R1: How to use OlympicCoder locally for coding?

upvoted an article 21 days ago

SmolLM - blazingly fast and remarkably powerful

upvoted an article 21 days ago

Welcome Gemma 3: Google's all new multimodal, multilingual, long context open LLM

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kargarisaac's activity

upvoted an article 14 days ago

Article

Open R1: How to use OlympicCoder locally for coding?

14 days ago

• 56

upvoted 2 articles 21 days ago

Article

SmolLM - blazingly fast and remarkably powerful

Jul 16, 2024

• 349

Article

Welcome Gemma 3: Google's all new multimodal, multilingual, long context open LLM

22 days ago

• 363

upvoted a collection 23 days ago

GraphRAG Papers

Collection

Research relating graphs and GenAI. For discussion, find dedicated threads on https://discord.gg/graphrag • 43 items • Updated 16 days ago • 28

reacted to burtenshaw's post with 🚀 about 1 month ago

Post

7421

AGENTS + FINETUNING! This week Hugging Face learn has a whole pathway on finetuning for agentic applications. You can follow these two courses to get knowledge on levelling up your agent game beyond prompts:

1️⃣ New Supervised Fine-tuning unit in the NLP Course https://huggingface.co/learn/nlp-course/en/chapter11/1
2️⃣New Finetuning for agents bonus module in the Agents Course https://huggingface.co/learn/agents-course/bonus-unit1/introduction

Fine-tuning will squeeze everything out of your model for how you’re using it, more than any prompt.