توی این ویدیو سعی کردم که به صورت ساده، LLM رو توضیح بدم.
این ویدیو، خلاصهای از صحبتهای Andrej Karpathy که توی یوتیوبش منتشر کرده بود هست.
Chapters
00:00 - Intro
00:20 - Andrej Karpathy
02:41 - Why do we need LLMs
06:15 - Pre-training
08:40 - Post training
10:00 - Hallucination
18:00 - Reinforcement Learning
22:00 - RLHF
24:00 - Now Vs Future
Links
Andrej Karpathy's Video: https://www.youtube.com/watch?v=7xTGNNLPyMI
ChatGPT https://chatgpt.com/
FineWeb (pretraining dataset): https://huggingface.co/spaces/Hugging...
Tiktokenizer: https://tiktokenizer.vercel.app/
Transformer Neural Net 3D visualizer: https://bbycroft.net/llm
llm.c Let's Reproduce GPT-2 https://github.com/karpathy/llm.c/dis...
Llama 3 paper from Meta: https://arxiv.org/abs/2407.21783
Hyperbolic, for inference of base model: https://app.hyperbolic.xyz/
InstructGPT paper on SFT: https://arxiv.org/abs/2203.02155
HuggingFace inference playground: https://huggingface.co/spaces/hugging...
DeepSeek-R1 paper: https://arxiv.org/abs/2501.12948
TogetherAI Playground for open model inference: https://api.together.xyz/playground
AlphaGo paper (PDF): https://discovery.ucl.ac.uk/id/eprint...
• Lee Sedol vs AlphaGo Move 37 - https://www.youtube.com/watch?v=HT-UZkiOLv8
LM Arena for model rankings: https://lmarena.ai/
AI News Newsletter: https://buttondown.com/ainews
LMStudio for local inference https://lmstudio.ai/