Reference implementation for Stability AI's diffusion models: SDXL base/refiner/Turbo for text-to-image, plus Stable Video Diffusion, SV3D, and SV4D for image-to-video and 4D synthesis. A modular engine separates samplers, guiders, and conditioners.
Trains LLMs with RLHF at scale by splitting actor, critic, reward, and reference models across separate GPU groups via Ray, with vLLM-accelerated generation and DeepSpeed ZeRO-3. Supports PPO, GRPO, REINFORCE++, DPO, plus async and agentic multi-turn RL.
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.
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.
Generates expressive multilingual speech from text, with sub-word control over prosody and emotion via inline tags like [whisper] or [angry]. Handles multi-speaker, multi-turn dialogue; the weights ship under a research-only license.
Terminal CLI for on-device Whisper ASR using Hugging Face Transformers + Optimum, with optional Flash Attention 2, batching, and diarization support — focused on high-throughput transcription on NVIDIA GPUs and Apple Silicon (mps).
Provides a 200k-example filtered conversational dataset derived from UltraChat for supervised fine‑tuning and generation‑ranking of chat models. Stored in parquet with four splits and used as part of Zephyr‑7B‑β training data.
Routes LLM and agent decisions through semantic similarity instead of waiting for full generations, useful for intent routing, tool selection, guardrails, and multimodal handling.
Provides a self-hosted inference engine that serves all models an agent needs—embeddings, retrieval/reranking, document-to-markdown OCR, structured extraction, content-safety scoring, and LLM generation—through an OpenAI-compatible API. Bundles a 100+ model catalog, SDKs, and production deployment tooling.
Multilingual automatic speech recognition and speech-translation model that transcribes and translates audio. Trained on a mix of weakly labeled and pseudo-labeled data (1M + 4M hours), uses 128 Mel bins and adds a Cantonese token, and supports timestamps and long-form chunking for offline ASR and translation.
Performs speaker diarization (who spoke when) with pyannote-audio: combines voice-activity detection, speaker-change and overlapped-speech detection to produce time-stamped speaker segments; compatible with Hugging Face Endpoints and ASR pipelines.
Collection of runnable model implementations — LLaMA, Mistral, Stable Diffusion, Whisper, CLIP, plus LoRA fine-tuning — ported to the MLX array framework so they run natively on Apple silicon's unified memory rather than CUDA.