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Fine-tunes and deploys 600+ LLMs and 400+ multimodal models in one framework, with SFT, pretraining, RLHF (DPO, PPO, GRPO), and lightweight methods like LoRA and QLoRA. Adds Megatron parallelism, vLLM/SGLang/LMDeploy inference, and a training web UI.
Runs Stable Diffusion XL behind a Midjourney-style interface, hiding samplers, model swaps, and LoRA weights. A built-in GPT2 expander rewrites prompts into richer styling, and it works fully offline on as little as 4GB of Nvidia VRAM.
Applies deep learning workflows to geospatial data, covering imagery search, dataset preparation, model training, inference, visualization, and QGIS integration for remote sensing.
Chat with your documents via retrieval-augmented generation; each answer carries inline citations and a built-in viewer highlights the cited PDF passage. Pairs full-text with vector search and runs on OpenAI, Azure, Cohere, Ollama, or local models.
Gives AI agents persistent long-term memory: ingests documents in any format and continuously builds a self-hosted knowledge graph fusing vector embeddings, graph reasoning, and ontology grounding, so agents recall and reason over connected facts.
Cross-platform downloader that uses AI-assisted chunking and acceleration to improve success rates across protocols. Supports HTTP/FTP/M3U8/MPEG‑DASH/Magnet/BT plus YouTube/Bilibili parsing, a browser extension, aria2-compatible RPC and an Android client — aimed at multi-protocol, long-running and streaming download tasks.
Runs open-weight LLMs (Llama, Gemma, Qwen, GGUF) offline on your machine, with an optional bridge to OpenAI/Anthropic/Mistral. Exposes an OpenAI-compatible API at localhost:1337, so SDK code built for OpenAI switches by changing one base URL.
Detects file content types with a compact deep‑learning model that runs in milliseconds on a single CPU. Trained on ~100M samples across 200+ content types; offered as a Rust CLI plus Python, JS, and Go bindings for large‑scale security and file‑routing use.
Self-hostable platform for building enterprise GenAI apps with visual workflow orchestration — loops, parallelism, human-in-the-loop — plus RAG, agents, unified model management, and in-house OCR for handwriting and rare characters.
Role-playing LLM agents — CEO, CTO, programmer, tester — collaborate through staged dialogues to turn a one-line prompt into a working software project. Now generalized into a zero-code platform for building custom multi-agent workflows beyond coding.
Converts microphone or streamed audio to text with sub-second latency, pairing WebRTC/Silero voice-activity detection and wake-word activation with swappable local backends — faster-whisper by default, plus whisper.cpp, Moonshine, and sherpa-onnx.
Agent framework for building tool-using applications on Qwen 3+ LLMs. Provides function calling, MCP, a Dockerized code interpreter, and RAG over documents up to 1M tokens; powers the Qwen Chat backend and a Chrome browser-assistant extension.