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Tags: LLM tools
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1–24 of 26 · Most stars

[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.

TranslatedFirefly: a large model training tool that supports training large models such as Qwen2.5, Qwen2, Yi1.5, Phi-3, Llama3, Gemma, MiniCPM, Yi, Deepseek, Orion, Xverse, Mixtral-8x7B, Zephyr, Mistral, Baichuan2, Llma2, Llama, Qwen, Baichuan, ChatGLM2, InternLM, Ziya2, Vicuna, Bloom, etc.

🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications

Self hosted, real-time digital human agent platform. Build voice-first AI agents with WebRTC, persona memory, tools, RAG, and optional digital-human video.

  • ai-agents
  • ai-companion
  • digital-human
  • digital-life

Millisecond decisions, any domain: a 0.8B open "System 1" model that picks between your options with calibrated probabilities. One base, swappable LoRA adapters, on your own hardware.

Open source, privacy-first Voice of Customer analytics. A self-hosted alternative to Enterpret and Unwrap that strips PII from feedback before any LLM sees it.

🍦 Speech-AI-Forge is a project developed around TTS generation model, implementing an API Server and a Gradio-based WebUI.

  • chattts
  • ssml
  • tts
  • chattts-forge

A 7-layer memory operating system for Hermes Agent — persistent memory with Qdrant, structured facts, fabric recall, auto-curated wiki, and surgical context injection. Runs locally, any LLM provider.

  • ai-memory
  • context-injection
  • docker
  • ground-truth

🔥 The first-ever interactive streaming video generation benchmark.

  • avatar-performance
  • interaction-streaming-video
  • real-time-video-editing
  • streaming-video-generation

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.