sft

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.

BoDmagh dataset is a Supervised Fine-Tuning (SFT) dataset for the Darija language

Tool-native dataset generation skill for Codex, Claude Code, and Antigravity with SFT/DPO pipelines, verification, deduplication, and flexible export.

Multi-node distributed LLM training framework

This open-source project delivers a complete pipeline for converting multi-page documents (PDFs/images) into structured JSON using Vision LLMs on Amazon SageMaker. The solution leverages the SWIFT Framework to fine-tune models specifically for document understanding tasks.

Fine-tune a local LLM on your own chat history to mimic how you write — an AI doppelganger / digital-twin toolkit built on LLaMA-Factory (LoRA SFT).

Hotel-domain conversational assistant using Qwen2.5-7B-Instruct, focusing on practical, reproducible fine-tuning. It supports SFT + LoRA for a stable baseline, SFT + QLoRA for 7B model training with 4-bit quantization under limited GPU memory, and DPO to enhance responses via human preference pairs

Advanced LLM fine-tuning techniques: SFT (LoRA, QLoRA, DoRA, P-/Prefix-Tuning), GRPO, DPO, ORPO, KTO & PPO; composable correctness/format rewards + LLM-as-a-Judge evals (DeepEval, Evidently AI) across math, multi-hop, medical & general QA on Llama 3, Mistral, Phi-4, Gemma & Qwen3. Built on TRL, PEFT & Unsloth.

Different post-training techniques for LLMs, including: SFT, DPO and Online RL