Discover the Best AI Resources
Curated essentials, no noise — just what matters
Performs feed‑forward streaming 3D reconstruction from image sequences, combining coordinate grounding, dense geometric cues and trajectory memory to correct long‑range drift; uses paged KV‑cache attention for ~20 FPS inference at 518×378 and supports sequences >10,000 frames.
Runs multiple AI agents in parallel inside a single macOS browser, giving each agent an isolated Space that can use your real logins without touching your tabs; controllable via an ego-browser JavaScript skill to perform web automation with fewer tokens and faster task completion.
Clinical question-answering model for psychological support in obesity weight-management. Integrates UK Biobank population evidence to produce clinically interpretable, stigma-aware responses that help clinicians identify distress, prompt screening, and suggest appropriate referrals.
Provides 207k+ LLM-generated agent trajectories of code edits and tool interactions for training and evaluating software-engineering agents. Collected via OpenHands and SWE-agent using Qwen3.5-122B and MiniMax-M2.5, multilingual across nine languages and released under CC BY 4.0.
Generates editorial-quality diagrams as self-contained HTML files with inline SVG across 27 visual types; includes brand onboarding, agent-skill integrations (Claude Code, Codex, Pi), draw.io/Mermaid import, and static-first output with optional accessible motion.
Drafts multiple tokens in parallel with a lightweight block-diffusion drafter to enable speculative decoding for faster LLM inference. Designed to pair with Qwen3.6-35B-A3B and reports up to ~2.9× throughput improvements on common benchmarks.
A healed 64-layer 'frankenmerge' that stacks two Qwen3.5-derived finetunes into an ~18B GGUF model for multilingual text generation, reasoning, and reliable code/frontend output. Healed with a 1000-step QLoRA to reduce layer-boundary artifacts and targeted to run on 12–16 GB GPUs.
Unifies multimodal understanding, reasoning, and image generation in a single end-to-end architecture using the NEO-unify paradigm. Models pixels and words jointly without a separate visual encoder, and provides interleaved image–text generation, infographic editing, and GGUF/low‑VRAM inference options.
Detects and masks personally identifiable information (PII) in text using a bidirectional token-classification model for high-throughput, on‑premises sanitization. Key traits: 1.5B parameters, 128k-token context, Apache 2.0 license, and tunable precision/recall operating points.
An uncensored, fully unlocked GGUF port of Qwen 3.6‑35B‑A3B for local multimodal (text+image) inference, offering K_P 'Perfect' quant variants (Q8–Q2) and an mmproj for vision. Suited for offline research and experimentation; not for use-cases requiring safety filters.
Provides a cleaned, SFT-ready collection of ~746k GLM-5.1 reasoning traces for instruction tuning and reasoning distillation. Normalizes varied chain-of-thought formats into a single conversations/input/output schema and preserves four focused subsets (main, PHD-Science, Multilingual‑STEM, Math).