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The ultimate guide to fine tuning.pdf
15.2 MB
πŸ”– The Big Book on Fine-Tuning LLMs

A free 115-page book dedicated to the retraining of large language models. πŸ“š

It's suitable for those who want to understand how to prepare datasets, configure training, and improve the quality of LLMs for their tasks. πŸš€

#LLM #FineTuning #AI #MachineLearning #DataScience #Tech

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πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
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πŸ”– LLM Scraper β€” parsing websites through neural networks

The tool allows you to convert any web pages into structured data using LLM.

Useful for data collection, site monitoring, and preparing datasets without writing complex parsers.

⛓️ Link to GitHub: https://github.com/mishushakov/llm-scraper

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⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
πŸ”‘ Use code: PRESALE-BOOK-WAVE-2GFG
πŸ‘‰ https://helloencyclo.com/?ref=HUSSEINSHEIKHO

#LLM #Scraper #WebScraping #DataCollection #AI #Automation
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A new collection of free courses has been added:

πŸ”— https://github.com/dair-ai/ML-Course-Notes

Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. πŸ“š

Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. 🧠

What's inside:

β€’ Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
β€’ A table with lectures, descriptions, videos, notes, and authors
β€’ Links to the original lectures and accompanying notes
β€’ WIP markers for incomplete materials
β€’ Instructions for contributors on adding and improving notes

The idea was appreciated. πŸ‘

Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. πŸ—ΊοΈ

#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource

✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
πŸ”‘ Use code: PRESALE-BOOK-WAVE-2GFG
πŸ‘‰ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Stop studying LLM from random articles and videos that only explain individual pieces of the puzzle.

πŸ“š LLM from Scratch β€” this is a practical course on PyTorch for those who want to understand the entire path of modern LLMs: from the first Transformer block to RLHF.

Instead of endless theory, here we gather a complete model training chain:

πŸ”Ή Pretraining β†’ Finetuning β†’ Alignment in one course
πŸ”Ή Transformer from scratch: positional embeddings, self-attention, multi-head attention, MLP, residual connections, LayerNorm, and full Transformer blocks
πŸ”Ή Own training loop without Trainer magic: tokenization, batches, cross-entropy, validation loss, text generation
πŸ”Ή Modern architecture improvements: RMSNorm, RoPE, SwiGLU, KV Cache, sliding-window attention, and streaming cache
πŸ”Ή Full section on alignment: SFT, reward models, PPO-style RLHF, and GRPO with an analysis of how it looks in the training loop in practice

πŸ”— [LLM from Scratch](https://github.com/vivekkalyanarangan30/llm_from_scratch)

#LLM #PyTorch #MachineLearning #DeepLearning #AI #Transformer

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⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
πŸ”‘ Use code: PRESALE-BOOK-WAVE-2GFG
πŸ‘‰ https://helloencyclo.com/?ref=HUSSEINSHEIKHO