AI Dataset2026
Provides 4,868 Turkish instruction examples with explicit chain-of-thought traces (<think>...</think>) in a messages-format JSONL for training and evaluating step-by-step reasoning of Turkish LLMs; culturally localized and Apache-2.0 licensed.
AI Dataset2026
Provides a near-deduplicated, quality-filtered 15.9 TB training subset of GitHub source code grouped by repository, with inline UTF‑8 file contents and repo metadata for pre-training and analysis of code LLMs; cutoff Aug 7, 2025, ODC-By license.
AI Model2026
A text-only open-weight MOE code model (35B total, 3B active) fine-tuned with SFT+RL for agentic coding; achieves strong agentic-code benchmarks, supports 262k context and deployment via Transformers/vLLM; vision weights are not included.
AI Dataset2026
Evaluates atomic visual perception of multimodal LLMs using 3,000 short visual questions that isolate ten perceptual skills. Built from an error taxonomy across 42 benchmarks, capability-balanced and accompanied by a model leaderboard.
AI Dataset2026
Curated set of 20,000 native 24×24 pixel-art sprites with two-level semantic taxonomy labels for tiny text-to-image and discrete visual modeling. Rebalanced, rights-conscious subset with ≤5 colors per sprite and stratified train/val/test splits.
AI Dataset2026
Consolidated dataset of detection, visual grounding and pointing annotations with indexed WebDataset image shards and Megatron‑Energon training metadata. Covers diverse visual domains (COCO, RefCOCO, driving, GUI, documents) and uses a normalized spatial grid for cross‑domain vision–language grounding training.
AI Model2026
Open-weight multimodal Mixture-of-Experts LLM with native vision and a 1,048,576-token context window. 2.8T parameters (104B activated), MXFP4 quantization, released for agentic long-horizon coding, knowledge work, and vision-in-the-loop workflows.