AI Rank
中文
← Open Source
rohan-paul

LLM-FineTuning-Large-Language-Models

LLM (Large Language Model) FineTuning.

TutorialsLLM fundamentalsJupyter Notebook
Open on GitHub
Momentum
+0stars in 24 hours0.0%
578
Stars
137
Forks
+0
This week
2
Contributors
Created 2023-10-22 · Updated 2026-09-09 · #16681 today
Top developers
rohan-pauleltociear

rohan-paul/LLM-FineTuning-Large-Language-Models is ranked 16,681 with 578 stars.

Same-category comparison

rohan-paul/LLM-FineTuning-Large-Language-Models is ranked 16,681 among these 8 peers; zjhellofss/KuiperLLama is ranked 16,684.

Same-category comparison
NameRankMetrics
the-ai-merge/multimodal-agents-course16,632
Language:
Python
Stars:
581
Forks:
149
Description:
An MCP Multimodal AI Agent with eyes and ears.
MazzaWill/neo4j-python-pandas-py2neo-v316,640
Language:
Python
Stars:
580
Forks:
187
Description:
Excel-to-Neo4j knowledge graph examples: legacy py2neo v3 plus modern Neo4j GraphRAG/vector search.
claudio-silva/claude-artifact-runner16,644
Language:
TypeScript
Stars:
580
Forks:
127
ukairia777/tensorflow-nlp-tutorial16,650
Language:
Jupyter Notebook
Stars:
580
Forks:
284
zjhellofss/KuiperLLama16,684
Language:
C++
Stars:
578
Forks:
148
persistforever/cifar10-tensorflow16,699
Language:
Python
Stars:
577
Forks:
208
zsdonghao/deep-learning-book16,743
Stars:
575
Forks:
269
24kchengYe/human-skill-tree16,774
Language:
TypeScript
Stars:
572
Forks:
30
Description:
🌳 AI-Powered Skill Tree for Lifelong Human Learning. 30+ skills from K-12 to career & social intelligence, built on cognitive science.
Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguageJupyter Notebook
CategoryTutorials
SubcategoryLLM fundamentals
KeywordsFinetuning
Stars578
Forks137
Contributors2
Created date2023-10-22
Updated date2026-09-09
Stars in 1 day0
Stars in 7 days0
Rank16,681
Previous rank16,470
Rank change-211
7-day stars rank15,664
Previous 7-day stars rank15,671
7-day stars rank change7
Total stars rank17,288
Previous total stars rank17,261
Total stars rank change-27
CountryIndia
README summary

LLM (Large Language Models) FineTuning Projects and notes on common practical techniques Find me in Twitter 📚 I write daily for my 112K+ readers on actionable AI developments. | | 📌 Why we need to identify for LoRA/QLoRA| | 📌 Evaluate Token per sec| | 📌 traversing through nested attributes (or sub-modules) of a PyTorch module| | 📌 Implementation of Sparse Mixtures-of-Experts layer in PyTorch from Mistral Official Repo| | 📌 Util method to extract a specific token's representation from the last hidden states of a transformer model

. | | 📌 Convert PyTorch model's parameters and tensors to half-precision floating-point format| | 📌 Quantizing 🤗 Transformers models with the GPTQ method| | 📌 Quantize Mixtral-8x7B so it can run in 24GB GPU| | 📌 What is GGML or GGUF in the world of Large Language Models ?

Frequently asked questions

How many stars and forks are recorded?

rohan-paul/LLM-FineTuning-Large-Language-Models has 578 stars and 137 forks.

What is the repository rank?

rohan-paul/LLM-FineTuning-Large-Language-Models is ranked 16,681.

What language and category are recorded?

rohan-paul/LLM-FineTuning-Large-Language-Models has 578 stars, uses Jupyter Notebook and belongs to Tutorials.

Which repository is closest in rank?

rohan-paul/LLM-FineTuning-Large-Language-Models is compared with zjhellofss/KuiperLLama, ranked 16,684 with 578 stars.

README

LLM (Large Language Models) FineTuning Projects and notes on common practical techniques

Find me in Twitter

📚 I write daily for my 112K+ readers on actionable AI developments. Get a 1300+ page Python book as soon as you subscribing (its FREE) ↓↓)

 

Fine-tuning LLM (and YouTube Video Explanations)

Notebook 🟠 YouTube Video
Finetune Llama-3-8B with unsloth 4bit quantized with ORPO
Llama-3 Finetuning on custom dataset with unsloth
CodeLLaMA-34B - Conversational Agent
Inference Yarn-Llama-2-13b-128k with KV Cache to answer quiz on very long textbook
Mistral 7B FineTuning with_PEFT and QLORA
Falcon finetuning on openassistant-guanaco
Fine Tuning Phi 1_5 with PEFT and QLoRA
Web scraping with Large Language Models (LLM)-AnthropicAI + LangChainAI

Fine-tuning LLM

Notebook Colab
📌 Gemma_2b_finetuning_ORPO_full_precision
📌 Jamba_Finetuning_Colab-Pro
📌 Finetune codellama-34B with QLoRA
📌 Mixtral Chatbot with Gradio
📌 togetherai api to run Mixtral
📌 Integrating TogetherAI with LangChain 🦙
📌 Mistral-7B-Instruct_GPTQ - Finetune on finance-alpaca dataset 🦙
📌 Mistral 7b FineTuning with DPO Direct_Preference_Optimization
📌 Finetune llama_2_GPTQ
📌 TinyLlama with Unsloth and_RoPE_Scaling dolly-15 dataset
📌 Tinyllama fine-tuning with Taylor_Swift Song lyrics

LLM Techniques and utils - Explained

LLM Concepts
📌 DPO (Direct Preference Optimization) training and its datasets
📌 4-bit LLM Quantization with GPTQ
📌 Quantize with HF Transformers
📌 Understanding rank r in LoRA and related Matrix_Math
📌 Rotary Embeddings (RopE) is one of the Fundamental Building Blocks of LlaMA-2 Implementation
📌 Chat Templates in HuggingFace
📌 How is Mixtral 8x7B is a dense 47Bn param model
📌 The concept of validation log perplexity in LLM training - a note on fundamentals.
📌 Why we need to identify target_layers for LoRA/QLoRA
📌 Evaluate Token per sec
📌 traversing through nested attributes (or sub-modules) of a PyTorch module
📌 Implementation of Sparse Mixtures-of-Experts layer in PyTorch from Mistral Official Repo
📌 Util method to extract a specific token's representation from the last hidden states of a transformer model.
📌 Convert PyTorch model's parameters and tensors to half-precision floating-point format
📌 Quantizing 🤗 Transformers models with the GPTQ method
📌 Quantize Mixtral-8x7B so it can run in 24GB GPU
📌 What is GGML or GGUF in the world of Large Language Models ?

Other Smaller Language Models

Nearby in the ranking
Similar items