Tag
Explore by tags
A small image-folder dataset for multimodal/vision model safety benchmarking, containing under 1,000 curated images with annotations to exercise safety-related model behaviours; licensed CC BY 4.0 and hosted on HuggingFace.
A reasoning-enhanced Mixture-of-Experts (MoE) LLM fine-tuned for multimodal image-text-to-text tasks and long-context reasoning; built on Qwen3.6-35B-A3B with LoRA and released as an experimental GGUF community model.
Open egocentric multimodal dataset for embodied AI and robot learning captured on commodity iPhone Pro: ~200 hours and ~10M RGB frames with LiDAR depth, ARKit 6‑DoF poses, IMU, two‑hand MANO mocap, room meshes, and hierarchical action captions.
Labeled Vietnamese handwritten line images paired with text transcriptions for training and evaluating OCR/text-recognition models. Stored in Parquet (optimized) with a dataset size in the 10K–100K sample range, suitable for model training and benchmarking.
Provides a curriculum-aligned knowledge graph extracted from Chinese K–12 textbooks and accompanying benchmarks and training data to evaluate and train educational LLMs. Releases a 23,640-question multi-select benchmark and a 7,335-sample graph-guided training corpus with multimodal VQA pairs and the full construction pipeline.
Processes text and images to produce conversational, reasoning-focused multilingual outputs for agentic workflows. Built as a sparse MoE decoder (25B active / 218B total parameters) with 128K context and available in BF16/FP8/W4A4 quantizations to balance quality and deployability.
Provides a quantized GGUF build of Qwen3.6‑27B with MTP (multi‑token prediction) support for faster local inference. Packaged for GGUF-compatible runners (llama.cpp) and Hugging Face/transformers workflows, with deployment notes for CPU/GPU and vLLM/SGLang integration.
Collection of 1,000 AI-generated dreamcore aesthetic images (2K JPEGs, numbered 001–1000) intended for creative prototyping and visual research. Images were produced with GPT Image 2 and released under an MIT license.
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.
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).
Provides 100,000 generated low-quality↔high-quality image pairs created with modern multi-frame/multi-modal models to boost generalization of image restoration methods; includes train/test JSONL lists, baseline training code, and pretrained checkpoints under CC BY‑NC‑ND 4.0.
Automates end-to-end web workflows from browser screenshots by emitting pixel-grounded actions (click, type, scroll, visit, search). Vision-first multimodal agent fine-tuned from Qwen3.5-27B with critical-point safety checks; intended for sandboxed, human-supervised deployments.