AI Video2026
Turns a short prompt plus aspect ratio and duration into a structured, shot-by-shot audio-video description for text-to-audio-video generation. A PEFT LoRA on Qwen3.6-27B that expands timing, camera motion, continuity, and synchronized diegetic/non‑diegetic sound; text-only and requires MiniMax-H3 + LightX2V to produce final AV.
AI Dataset2026
10,000-hour head-and-wrist egocentric dataset pairing synchronized head and wrist video with left/right 3D hand pose and optional full-body pose; provided in LeRobot/MCAP formats with episode-level semantic annotations and automated de-identification.
AI Video2026
Packaged diffusers checkpoint of MiniMax H3 for image/text-to-short-video generation with native stereo audio; provided for direct use in diffusers image-to-video pipelines and aimed at easy integration into prototyping and production workflows.
AI Video2026
Provides ComfyUI-compatible conversions and LoRA adapters of the MiniMax‑H3 video+audio generative model, with example presets and demo videos to run short stereo audio+video inference inside ComfyUI workflows.
AI Audio2026
Generates complete songs (up to five minutes) from lyrics and a music description, producing 32 kHz stereo WAV with expressive vocals and long-range musical structure. Uses hierarchical LLMs fused with flow-matching/Flow-VAE synthesis for coherent arrangement and timbre; requires CUDA and integrates with Diffusers and SGLang-Omni.
AI Dataset2026
Provides raw, unscripted first-person household video footage for training vision and embodied AI models. Released incrementally on Hugging Face in WebDataset shards with metadata parquets under Apache‑2.0; current raw tier contains ~7,834 hours (≈397k videos).
AI Dataset2026
Provides 90,000 hours of head-mounted egocentric video paired with synchronized 3D hand pose and an optional 3D full‑body pose add-on, with event-level semantic labels available as a complimentary layer — designed for embodied AI and robotics training at scale.
AI Dataset2026
100-hour, single-narrator Egyptian Arabic speech corpus with 15,653 aligned clips at 24 kHz for TTS and ASR fine-tuning; studio-consistent audio, machine-generated undiacritized transcripts, CC BY-NC 4.0 (research/non-commercial use).
AI Model2026
A MoE causal large language model for long-horizon agents, coding, and multi-step reasoning: 2.4T parameters (95B activated), native 262,144-token context (extensible to 1,010,000), multi-token prediction, and configurable thinking-mode reasoning controls.
AI Model2026
FP8-quantized checkpoint of the Qwen3.8 text-only causal LLM (2.4T params, 95B activated) for text-generation; preserves near-original performance, supports very long contexts (262k–1M), Mixture-of-Experts architecture, and is compatible with vLLM/SGLang/TokenSpeed. Thinking mode and preserve_thinking are enabled by default.
AI Dataset2026
Human-annotated text dataset that labels perceived “AI slop” with a continuous human slop_score (-1 / 0 / +1) plus provenance metadata (source_dataset, source_row_id, content_hash). Collected via Bench Labs SlopFinder from public datasets for training classifiers and studying subjective perception.
AI Model2026
A 29.6B-parameter multimodal causal language model with a dedicated ViT-G/14 perception encoder for running agentic, tool-using, multimodal reasoning locally on consumer hardware. Offers 4-bit quantized weights and a DFlash drafter for speculative decoding to reduce memory and speed up generation.