fine-tuning

A distributed training framework for large language models powered by Lightning.

[AAAI'25] The implementation of paper "Federated Foundation Models on Heterogeneous Time Series" | The first work to explore time series foundation models on federated setting.

[ACL2023] Preserving Commonsense Knowledge from Pre-trained Language Models via Causal Inference

DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agents

MinimalGPT is a concise, adaptable, and streamlined code framework that encompasses the essential components necessary for the construction, training, inference, and fine-tuning of the GPT model. This framework is implemented exclusively using Keras and TensorFlow, ensuring compatibility and coherence within the broader deep learning ecosystem.

A structured knowledge base for large language model technologies, covering LLMs, Agents, RAG, model training, evaluation methodologies, and AI engineering practices.

In this implementation, using the Flan T5 large language model, we performed the Text Classification task on the IMDB dataset and obtained a very good accuracy of 93%.

A curated list of the best AI resources, courses, tools, and repositories. Covering Generative AI (GenAI), LLMs, RAG, AI Agents, Prompt Engineering, and more. Your go-to cheat sheet for all things AI.

This repository contains code for fine-tuning the Whisper speech-to-text model.

Implementation for the different ML tasks on Kaggle platform with GPUs.

Over 60 figures and diagrams of LLMs, quantization, low-rank adapters (LoRA), and chat templates FREE TO USE in your blog posts, slides, presentations, or papers.

The Ultimate Developer Experience Platform for the Container Era

Train an LLM to generate cracked Manim animations for mathematical concepts.

Interview prep for LLM post-training, ML, system design, and coding — organized by career path.

🥉 Codalab-Microsoft-COCO-Image-Captioning-Challenge 3rd place solution(06.30.21)

Build a Large Language Model From Scratch

CyberBrain_Model is an advanced AI project designed for fine-tuning the model `DeepSeek-R1-Distill-Qwen-14B` specifically for cyber security tasks.

Code for TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning for Discrete Diffusion

OpenCLAW SEED — Autonomous self-evolving research agent with LoRA fine-tuning. Part of P2PCLAW ecosystem. Trains itself on research papers, improves over time. Apache 2.0.

Flan-t5-base model was fine-tuned on Nvidia Question and Answer Pair Dataset available on Kaggle. This is a beginner level project who wants to step in to the world of Large Language Models.