AI Model2026
A surgically modified Gemma 4 (12B) that removes refusal behavior while preserving benchmark parity; released as an uncensored research artifact with GGUF quantizations for local inference and red‑team/alignment evaluation.
AI Model2026
GGUF-format QAT (quantization-aware training) build of Gemma 4 12B that reduces memory needs for local or lightweight inference while preserving near bfloat16 quality. Ready for any-to-any conversational pipelines and ecosystem deployment.
AI Dataset2026
Provides page-level relevance judgments and full OCR'd annual-report text for KPI question answering and page retrieval benchmarking — supports retrieval (per-page qrels) and needle‑in‑a‑haystack numeric extraction over long documents, with eval and train configs.
AI Dataset2026
Pairs OCR-extracted annual-report text with ground-truth financial KPI values to benchmark LLM/table-QA and needle-in-a-haystack extraction tasks. Includes Markdown OCR (.mmd), page images for eval, and 31 KPI columns across multiple years—suited for KPI extraction, retrieval, and robustness testing.
AI Model2026
A GGUF release of Gemma 4 26B A4B (QAT) packaged by Unsloth for local multimodal inference — quantization-aware trained to keep near-bfloat16 quality while significantly lowering memory requirements, compatible with Transformers and Unsloth tooling.
AI Model2026
Code-focused sparse Mixture-of-Experts LLM designed for agentic coding and terminal/tool use, offering very long context (256K) and long outputs. Released with open weights under Apache-2.0 and optimized for transformers/vLLM workflows.
AI Model2026
Experimental, uncensored fine-tune of Google Gemma-4-12B-it that applies an 'abliteration' technique to remove refusal behaviors; intended for research and testing only and carries elevated safety and legal risks.
AI Dataset2026
Provides 1,036,431 identity–text–video triplets with per-video JSON annotations and reference keyframes to train and evaluate identity-preserving customized video generation models. Data is drawn from ~320K Pexels HD videos; videos must be downloaded separately per Pexels' terms.
AI Model2026
Adds discrete audio tokens and an audio encoder to a 30B MoE text LLM so a single model can perform ASR, speech translation, TTS, text-to-audio and speech-to-speech while preserving text reasoning and long-context capabilities; supports thinking/instruct modes and up to 1M-token context.
AI Model2026
Implements MXFP4 quantization on MoE experts plus a BF16 DFlash block-diffusion drafter to propose whole-token blocks for verification, cutting memory bandwidth and backbone forward passes for trillion‑parameter text generation—targeting long‑context, agent and code workloads.
AI Dataset2026
Provides 500+ hours of human whole-body teleoperation demonstrations for humanoid robot learning in real homes, with synchronized video, joint states, action traces and language annotations. Includes 23K+ episodes, fine-grained subtask labels, and raw ROS/MCAP plus compressed LeRobot formats.
AI Model2026
Generates text from interleaved text, image, and short-video inputs using discrete diffusion and block‑autoregressive multi‑canvas sampling; built on a sparse MoE (8/128) Gemma 4 backbone and optimized for low‑latency inference and very long contexts (up to 256K tokens).