AI Dataset2026
Provides one million executable, human-readable CadQuery construction sequences synthesized by an LLM-in-the-loop—each sample includes renders, STL/STEP exports, precomputed DINOv3 embeddings and a FAISS index. Designed for training and benchmarking text/image→3D and CAD-program generation models (Apache-2.0).
AI Dataset2026
Provides ~12.29M execution‑free agentic coding trajectories (≈112B tokens) sampled from 122K GitHub PRs to mid‑train code and agent models. Uses bash-only actions (grep, git, sed, etc.) so it scales without Docker; trajectories are unverified and intended for mid-training rather than final SFT.
AI Dataset2026
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.
AI Dataset2026
Provides 34k execution-style agent trajectories (11,766 issues) for supervised fine-tuning of code-focused LLMs. Each instance includes multi-step interactions, tool-call records, and final unified diffs; generated with Qwen3-Coder and released under permissive licenses for commercial use.
AI Client2026
Terminal-first developer workspace with an agentic AI side-panel that runs against your API keys or local models. Bundles a native PTY terminal, CodeMirror editor with AI edit diffs, file explorer, git history/graph, and a web preview in a ~7–8MB desktop app with no telemetry.
AI Dataset2026
Collects real-world developer–AI coding sessions with full transcripts, tool calls, agent thinking traces, Git commits, and agent vs. human code attribution. Packaged as Parquet tables (conversations, sessions, commits, checkpoints, repositories) for analysis of agent behavior and human–AI collaboration.
AI Model2026
Open-source Mixture-of-Experts LLM designed for extremely long-context (up to 1M tokens) text generation and agentic workflows; uses a hybrid attention + MTP design to reduce KV-cache footprint while enabling 42B active parameters and FP8 mixed-precision training.
AI Dataset2026
Provides 1.7M agent interaction traces in terminus-2 format for training and evaluating agentic LLMs and RL agents. Compiled from 219 source datasets across code repair, shell, math, competitive programming and general tasks; produced with the Harbor harness.
AI Dataset2026
Aggregates 750k+ Harbor-compatible agentic tasks from 100+ public sources (Parquet shards preserved). Includes tasks with and without verifiers for RL evaluation or SFT/datagen workflows, enabling reproducible trace generation.
AI Model2026
An uncensored, fine-tuned and GGUF-quantized variant of Qwen3.6-27B tailored for long-context, coding, vision and creative-writing use. Offers multiple NEO-CODE Di-Matrix quants (IQ2/IQ4/Q6/Q8), mmproj vision support and recommended inference settings for local servers.
AI Dataset2026
Early-preview (≈1.2k rows) dataset of agentic coding prompts and unedited model responses generated by DeepSeek‑V4‑Pro, covering real-world programming tasks across many languages. Intended for research, filtering, and model evaluation rather than production training without review.
AI Model2026
Generates high-fidelity 3D assets from a single image by back-projecting pixel-aligned features into 3D, preserving fine geometry and PBR textures; includes inference code and a Hugging Face demo—best suited for single-view object reconstruction.