AI Model2026
Reasoning-enhanced 27B dense LLM fine-tuned from Qwen3.6-27B and released in GGUF format for image-text-to-text and long-context reasoning. Augmented with Trace Inversion reconstructed chains, three-stage SFT curriculum and MTP/vision support; community research release.
AI Model2026
Provides a 1-billion-parameter English pretrained language-model checkpoint that uses a dual-timescale Hierarchical Reasoning Model to increase effective compute depth. It's a PrefixLM pre-alignment checkpoint with composite-prefix modes for chain-of-thought style outputs; not instruction-tuned and requires downstream SFT/RL for assistant use.
AI Model2026
W4A4-quantized build of a 25B-parameter multimodal LLM that produces text from image+text inputs and supports conversational tool use. Trades very small quality differences for much lower GPU memory and latency so inference can run on smaller accelerators (vLLM support).
AI Video2026
Generates minute-scale, 720p videos from a single image using a 2.6B image-to-video diffusion transformer with precise 6‑DoF camera control and an optional LTX‑2 refiner; designed for long-context, memory-efficient modeling but requires large refiner checkpoints (~41 GB).
AI Model2026
A GGUF-format 9B LLM fine-tuned for code generation and agentic tool-calling that uses Multi-Token Prediction (MTP) and draft heads to increase throughput and long-range planning. Intended for local inference and research/experimental coding workflows; Apache‑2.0 license.
AI Dataset2026
Dataset of 5,000 reconstructed chain-of-thought samples produced by trace‑inversion from Claude‑opus‑4.7 summaries — packaged for SFT/DPO fine‑tuning. Key features: reconstructed CoT traces, multilingual prompts, gzip .jsonl format. Best used for reasoning distillation and model-level supervision; synthetic traces may need extra verification.
AI Dataset2026
Provides 9,000 reconstructed chain-of-thought (CoT) SFT examples produced by trace inversion from Claude Opus 4.6 outputs for fine-tuning reasoning-capable LLMs. Multilingual, packaged as .jsonl.gz and SFT/DPO-ready; verify numeric/code cases before training.
AI Model2026
Provides a locally runnable 26.9B Qwen3.6 checkpoint that surgically reduces refusal behavior in weight space while preserving capability; ships bfloat16 safetensors and a GGUF quant ladder for local runtimes and red-team evaluation.
AI Dataset2026
RL training dataset for long-context language-model fine-tuning with ~23K samples and nine reward types, provided in Parquet with bilingual ground-truth and reward metadata for direct RL/bench evaluation.
AI Audio2026
Converts long-form multi-speaker audio/video into a compact, speaker-aware transcript with timestamps and anonymous speaker labels in one pass. Combines ASR and diarization in a single model, supports custom prompts/hotwords, and targets meetings, podcasts, interviews and long recordings.
AI Dataset2026
Supervised fine-tuning dataset of instruction-style examples in English and Chinese covering generation, QA, reasoning, math and code — targeted for SFT of 10–100B-parameter LLMs. Associated with arXiv:2602.09003; first published May 21, 2026.
AI Model2026
Fine-tuned reasoning model that speeds up structured multi-step outputs using Multi-Token Prediction (MTP) from a Qwen3.6-27B base. Produces more concise, faster generations for coding, DevOps, math, and constrained-format tasks; experimental community release for research and evaluation.