Navigating the World of AI, One Step at a Time
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Updated
Oct 25, 2024 - Jupyter Notebook
Navigating the World of AI, One Step at a Time
End to End Generative AI Industry Projects on LLM Models with Deployment_Awesome LLM Projects
Auto Data is a library designed for quick and effortless creation of datasets tailored for fine-tuning Large Language Models (LLMs).
🚀 Easy, open-source LLM finetuning with one-line commands, seamless cloud integration, and popular optimization frameworks. ✨
A Gradio web UI for Large Language Models. Supports LoRA/QLoRA finetuning,RAG(Retrieval-augmented generation) and Chat
Fine-tune Mistral 7B to generate fashion style suggestions
[NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
the small distributed language model toolkit; fine-tune state-of-the-art LLMs anywhere, rapidly
Medical Language Model fine-tuned using pretraining, instruction tuning, and Direct Preference Optimization (DPO). Progresses from general medical knowledge to specific instruction following, with experiments in preference alignment for improved medical text generation and understanding.
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
SEIKO is a novel reinforcement learning method to efficiently fine-tune diffusion models in an online setting. Our methods outperform all baselines (PPO, classifier-based guidance, direct reward backpropagation) for fine-tuning Stable Diffusion.
On Memorization of Large Language Models in Logical Reasoning
[EMNLP 2024] Quantize LLM to extremely low-bit, and finetune the quantized LLMs
Finetuning Google's Gemma Model for Translating Natural Language into SQL
A open-source framework designed to adapt pre-trained Language Models (LLMs), such as Llama, Mistral, and Mixtral, to a wide array of domains and languages.
qwen-1.5-1.8B sentiment analysis with prompt optimization and qlora fine-tuning
Code for fine-tuning Llama2 LLM with custom text dataset to produce film character styled responses
A curated list of Parameter Efficient Fine-tuning papers with a TL;DR
Finetuning LLMs + Private Data (Video 1/10) Basic
This repository contains code for fine-tuning the LLama3 8b model using Alpaca prompts to generate Java codes. The code is based on a Google Colab notebook.
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