Embodied AI2026
Reconstructs camera poses and dense 3D point clouds from video streams using a feed‑forward foundation model. Combines a Geometric Context Transformer (anchor + local window + trajectory memory) with paged KV‑cache attention to enable stable, long‑sequence streaming inference (~20 FPS at 518×378).
AI Model2026
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.
AI Model2026
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.
AI Model2026
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.
AI Dataset2026
About 9,700 synthetic full-page web screenshots with YOLO-format, pixel-aligned bounding boxes for 14 UI element classes, generated by LLM-augmented HTML and Playwright DOM extraction. Includes CC3M image injection to reduce visual gap; released for non-commercial research (CC BY-NC-SA 4.0).
AI Dataset2026
A 1.4M image–text style dataset for text-to-image generation and style transfer, produced by mapping 170K curated style prompts to 400K content prompts via Qwen-Image to yield strong intra-style consistency. Designed for training and evaluating style-aware generative models; license: other.
AI Model2026
A 27B multimodal causal language model with a vision encoder and native long-context support (262,144 tokens). Optimized for repository-level coding agents and multimodal understanding; includes preserved "thinking" traces, multi-token prediction (MTP), and deployment recipes for vLLM / SGLang / Transformers.
AI Dataset2026
Provides a large-scale multimodal embodied dataset (vision, depth, hand/arm kinematics, tactile) captured with an exoskeleton glove and egocentric sensors; organized as clip-level Zarr volumes for manipulation, imitation learning, and vision–action research. Includes both high-precision glove measurements and natural bare-hand clips; sizable storage required.
AI Model2026
Provides a locally runnable, refusal-free variant of Qwen3.6-27B with multiple K_P GGUF quantizations and mmproj multimodal support. The Aggressive flavor skips preambles on edgy prompts—use when you want direct/raw responses for local research, red‑teaming, or offline workflows.
AI Model2026
A vision-oriented foundation checkpoint for low-latency inference — DeepSeek V4 base in safetensors with FP8 optimizations. Designed for fast image generation and embedding use in inference pipelines; verify license and FP8/runtime compatibility before production use.
AI Model2026
Base image-generation foundation model tuned for visual search and prompt-guided synthesis, intended as a compact starting point for local inference or fine-tuning. Emphasizes easy integration into image pipelines and suitability for downstream adaptation.
AI Model2026
Unifies multimodal image understanding, text-to-image generation, and instruction-based editing in a single diffusion LLM using a Mixture-of-Experts backbone, SigLIP-VQ discrete tokenizer, and a distilled diffusion decoder enabling fast (8-step) decoding; full-generation needs ~47GB GPU RAM.