AI Infra2025
Runs and fine-tunes LLMs locally on Apple silicon via the MLX framework, pulling thousands of Hugging Face models with one command. Adds 4- and 8-bit quantization, LoRA and full fine-tuning, prompt caching, and distributed inference across Macs.
AI Dataset2025
Jake Poznanski, Jon Borchardt +7Allen Institute for Artificial Intelligence (AI2), AllenNLP / olmOCR team
Benchmark for evaluating OCR systems that convert PDFs and scans into Markdown and structured text: 1,403 PDFs and 7,010 unit tests covering text presence/absence, reading order, tables, and math formula accuracy. Diverse sources and ODC-BY-1.0 license for research use.
AI Agent2025
Autonomously executes diverse biomedical research tasks by combining LLM reasoning, retrieval-augmented planning, and code-based execution. Includes a web UI and Gradio demo, a curated Know‑How library, MCP integration, and a biology-tailored reasoning model (Biomni‑R0).
AI Client2025
Runs open-source LLMs and multimodal models entirely on mobile devices for offline, private inference. Offers Agent Skills, Thinking Mode, Ask Image, audio scribe, model management and benchmarks, with Gemma 4 and Hugging Face integration.
AI Dataset2025
Provides 5 million instruction–response pairs for supervised fine-tuning of code LLMs, with inputs, outputs, unit tests, and automated LLM judgments. Uses hybrid automated/synthetic generation and is released under CC BY 4.0 for large-scale SFT workflows.
AI Video2025
Clean-room, modular implementations of multi-object tracking algorithms — SORT, ByteTrack, OC-SORT, BoT-SORT, C-BIoU — behind one interface. Detector-agnostic: works with YOLO, DETR, or any bounding-box model via supervision.Detections.
AI Audio2025
Open-source TTS that clones a voice from a short reference clip across 23+ languages, with adjustable emotional intensity via exaggeration/cfg controls and a built-in Perth neural watermark on every output.
AI Video2025
Provides PyTorch code, pretrained checkpoints, and evaluation tooling for V-JEPA 2 — a Meta FAIR family of self-supervised video encoders and an action-conditioned world model. Includes training recipes, HuggingFace checkpoints, evaluation probes, and robot post‑training artifacts.
AI Image2025
Converts document images—scans, photos, born-digital PDFs—into structured text in two stages: first map layout and reading order, then parse each element (text, tables, formulas, figures) in parallel, each guided by its own task prompt.
AI Train2025
Enables bidirectional checkpoint conversion between Hugging Face and Megatron formats and provides a PyTorch-native training library with tensor/pipeline parallelism, FP8/BF16 mixed precision, SFT and PEFT (LoRA) support for large and multimodal models.
AI Dataset2025
Physics-aware simulated sensor dataset for training and evaluating autonomous-vehicle perception and control models. Includes multimodal sensor streams with physical-scene annotations intended for tasks that require grounding in real-world dynamics.
AI Infra2025
Extends RAG beyond text: parses PDFs and Office files containing images, tables, equations, and charts, then queries them through one multimodal knowledge graph. Built on LightRAG, it replaces separate parsing and retrieval tools.