fine-tuning

Docker image and scripts for training finetuned or completely personal Kaldi speech models. Particularly for use with kaldi-active-grammar.

Set of fast LINQ-like extension methods for arrays and lists. Fine-tune your code for the maximum performance.

Deterministic AI defense framework: immutable input filtering, n-model cryptographic hash consensus, and self-learning adaptive rules. Zero dependencies. Hardware-sealed. Patent Pending.

Collect and maintain high quality instruction finetune datasets in different domain and languages. 搜集並維護高品質各專業領域及語言的指令微調資料集

This repository provides an easy way to train your models on the datasets of DCASE task 1.

Investigating the role of pre-training dataset size and diversity on the performance of single-cell foundation models

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

Implementation of build an LLM from scratch by Sebastian Raschka.

Fine-tuning open-source large and small instruct/chat language models (LLMs & SLMs) from the Hugging Face Model Hub using public datasets.

A comprehensive GUI wrapper application for Apple's Foundation Models Adapter Training Toolkit, providing an intuitive interface for training LoRA adapters for Apple's on-device foundation models.

Fast, config-driven SDXL LoRA & DreamBooth fine-tuning — train from a single YAML file. QLoRA + torch.compile.

Deferred Continuous Batching in Resource-Efficient Large Language Model Serving (EuroMLSys 2024)

Official GitHub repository for Phison aiDAPTIV. NAND cache memory-boosted AI inference and LLM fine-tuning platform.

LLM-adaptive embeddings (Zero-shot / LoRA) with Generative Topic Modeling & Agent-based workflow for social science text mining

Code for reproducing the experiments on large-scale pre-training and transfer learning for the paper "Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images" (https://arxiv.org/abs/2106.00116)

A curated list of papers on graph transfer learning (GTL).

Implementation of TSDS: Data Selection for Task-Specific Model Finetuning. An optimal-transport framework for selecting domain-specific and task-specific training data to improve LLM finetuning and instruction tuning.

A feature-rich web application for automated news scraping and summarization. It allows users to enter article URLs, fetches the full content, and generates concise summaries. The system supports both local inference with custom models and remote deployment via FastAPI or Streamlit interfaces.

(WACV'24) Kaizen: Practical self-supervised continual learning with continual fine-tuning

jupyter notebooks to fine tune whisper models on Vietnamese using Colab and/or Kaggle and/or AWS EC2