Python 排行榜

🧠 AI Second Brain — 100% Local Knowledge Management Private, self-hosted second brain. Store, search, and synthesize documents, images, and ideas with local LLMs (LLaVA, CLIP) and PostgreSQL + pgvector. Features multimodal search, knowledge graphs, gDrive streaming, and real-time analysis — all offline, no API keys, no cloud, no limits.

Repository for the paper 'Enhancing Clinical Decision Support with Physiological Waveforms — A Multimodal Benchmark in Emergency Care'.

This is a cross-modal benchmark for industrial anomaly detection.

It shows how to use mutimodal and RAG based on multi-region LLM.

Multimodal Open Source Framework for Conversational Agent Research and Development.

PAFTS : Library That Preprocessing Audio For TTS.

Offline-first voice dictation, transcription, cleanup, and text-to-speech for macOS, iOS, and Android.

kospeech를 활용한 한국어 음성 인식 모델 개발

Speech to text to speech using Elevenlabs

Speech2Speech-AIAssistant; A lightweight, offline-capable voice assistant that listens for a wake phrase, converts speech to text, runs local or API-based intent handling, and replies with natural-sounding TTS. Built for quick local deployment, it supports configurable wake words, microphone I/O, and easy integration with custom actions or LLMs.

A collection of utilities for handling IPA phones.

A hybrid router that uses Spot GPU instances to reduce costs and Serverless GPUs for making Cold Starts faster.

a simple lightweight large language model pipeline framework.

🎈 Structure-aware adapter fine-tuning PLMs, with high training speed and impressive performance (Journal of Chemical Information and Modeling 2024).

Implementation of Bitune: Bidirectional Instruction-Tuning

A minimal tool to generate and validate datasets.

Turn documents into high-quality instruction datasets with grounding, quality filtering, deduplication, and provenance.

AnnoTheia is a data annotation toolkit that identifies when a person speaks in a scene and transcribes their speech, also offering flexibility to replace modules for different languages.

A complete, hands-on roadmap to becoming an AI Engineer, from Python basics to production RAG, Agents, and Fine-Tuning. 10 modules, 20+ notebooks, 15 real projects. Free, open source, built for the community.

A regularized self-labeling approach to improve the generalization and robustness of fine-tuned models