Popular GitHub Repositories for Parameter

?? 「大模型」2小时完全从0训练26M的小参数GPT！? Train a 26M-parameter GPT from scratch in just 2h!

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Use PEFT or Full-parameter to finetune 450+ LLMs (Qwen2.5, InternLM3, GLM4, Llama3.3, Mistral, Yi1.5, Baichuan2, DeepSeek-R1, ...) and 150+ MLLMs (Qwen2.5-VL, Qwen2-Audio, Llama3.2-Vision, Llava, InternVL2.5, MiniCPM-V-2.6, GLM4v, Xcomposer2.5, Yi-VL, DeepSeek-VL2, Phi3.5-Vision, GOT-OCR2, ...).

A Flexible and Powerful Parameter Server for large-scale machine learning

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

? 「大模型」1小时从0训练26M参数的视觉多模态VLM！? Train a 26M-parameter VLM from scratch in just 1 hours!

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)

An optimized deep prompt tuning strategy comparable to fine-tuning across scales and tasks

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO?

Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"

An autoML framework & toolkit for machine learning on graphs.

A plug-and-play library for parameter-efficient-tuning (Delta Tuning)

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

A curated list of prompt-based paper in computer vision and vision-language learning.

An implementation of Tacotron 2 that supports multilingual experiments with parameter-sharing, code-switching, and voice cloning.

A Pytorch implementation of Sparsely-Gated Mixture of Experts, for massively increasing the parameter count of language models