Python 排行榜

This repo contains the original implementation of VAuLT, the Vision-and-Augmented-Language Transformer. We provide instructions to download some multimodal social-media datasets, and scripts to experiment with. VAuLT is a stack of Transformers, a LM like BERT that preprocesses the text input of ViLT

[IEEE TMM 2024] IGReg: Image-Geometry-Assisted Point Cloud Registration via Selective Correlation Fusion

A Comprehensive Speech Processing Algorithms Library for research and production use

Local inference server for Apple Silicon — hot-swaps MLX models (LLM, vision, embeddings, TTS, STT) via OpenAI API

benchmark for Speech-to-Intent engines

DiscordNPC lets you interact with ChatGPT through a Discord voice channel, enabling a natural conversation.

Listen4Me bot converts audio messages into text.

Python SDKs for Speechmatics APIs

A small wrapper package around whisper-timestamped. Create force-aligned transcription TextGrids from raw audio!

Let your AI agent call your phone and talk to you — MCP servers for live, interruptible voice calls + tiered alerts, using free self-hosted pieces (pjsua2 + whisper.cpp + Linphone). No paid telephony, no extra API key.

I'm sorry, Dave. I'm afraid I can't let that spam call through. — Local AI answering service with voice cloning, call recording, and sub-second latency. Runs entirely on your GPU. No cloud. No per-minute billing. Just HAL.

An OpenAI Compatible API which integrates LLM, Embedding and Reranker. 一个集成 LLM、Embedding 和 Reranker 的 OpenAI 兼容 API

Source code for the paper: Hear Both Sides: Efficient Multi-Agent Debate via Diversity-Aware Message Retention

Drop-in OIDC & Google A2A auth + Weaviate memory for Ollama, vLLM and any local LLM server.

Calibrating LLMs with Information-Theoretic Evidential Deep Learning (ICLR 2025)

Multiple Choice Learning of Low Rank Adapters for Language Modeling

[CVPR 2025 Highlight] Meta LoRA / MetaPEFT: Meta-Learning Hyperparameters for Parameter-Efficient Fine-Tuning (LoRA, Adapter, Prompt Tuning) — Automatic hyperparameter optimization via bi-level meta-learning

Multi-scale Finetuning for Encoder-based Time Series Foundation Models

an easy way to create JSONL files for fine-tuning openai models.

Sparse Autoencoders (SAE) vs CLIP fine-tuning fun.