AI Model2026
Provides uncensored variants of Qwen3.8-27B modified with ARA (Arbitrary-Rank Ablation) to surgically remove refusal behavior, packaged as GGUF quant files for local llama.cpp inference. RVN applies two extra ARA passes that reduce harmful-prompt refusals to 0–1/100 with very low KL damage; intended for adult research/creative use and reduces safety guardrails.
AI Dataset2026
Provides 617.5 hours of high-precision optical motion-capture with synchronized object trajectories and standardized 55-joint BVH for whole-body and human–object interaction research. Frame‑LU indexed and paired with natural-language descriptions; designed for humanoid learning, motion priors, and interaction-aware benchmarks.
AI Dataset2026
Provides a machine-readable catalog of 117 AI/AX safety and deployment-readiness diagnostic criteria for assessing model intrinsic and serving/infrastructure risks. Includes MODEL-SCAN and AX-SCAN axes, bilingual source fields, per-item evidence guidance, severity/assurance metadata, and a CC BY-NC 4.0 release-candidate.
AI Model2026
Parses digital and camera-captured documents into structured outputs (text, layout, tables, formulas, figures) using a lightweight (~1.2B) open-source vision-language model. Uses geometry-aware modeling, multi-node consensus pseudo-labeling, and content-structure decoupling to handle warped, photographed, and digital pages.
AI Model2026
Provides locally runnable GGUF quantizations of Qwen3.8-27B with the MTP speculative-draft head preserved and a Heretic weight edit that substantially reduces refusal rate. Ships multiple quant sizes with published imatrix and perplexity measurements for local inference under Apache‑2.0.
Separates knowledge storage (a global Memory) from iterative reasoning operators (multiple Reasoners) to improve knowledge compression and inference efficiency; reports a 7B model matching baseline with 62.6% of training data and a 35B Intern-S2-Mobius achieving ~4x end-to-end speedup.
AI Model2026
Provides a full GGUF quant ladder of an "abliterated" Qwen3.8-27B for local llama.cpp inference — includes every K-quant, embedded MTP speculative head, and optional vision projectors; refusal behavior was reduced at the weight level, so validate before production.
AI Model2026
A 9B-parameter distillation that transfers chain-of-thought reasoning from Qwen3.8 into the Qwen3.5-9B architecture for single‑GPU deployment; trained on ~70,000 teacher traces, it offers 262k-token context, native function-calling, and improved MMLU performance.
AI Model2026
An FP8-quantized, uncensored mirror of Qwen3.8-27B for image-text-to-text tasks — preserves native multimodal vision and very long context while targeting transformers/vLLM deployments; intended for offline testing and red-teaming and may bypass built-in safety filters.
AI Dataset2026
An index of Cara App content: metadata and CDN URLs for ~3.43M posts, 8.52M master artworks (~12M image links). Includes an SQLite catalog and Parquet exports but does not include image bytes — only links and metadata for analysis and search.
AI Model2026
A Gated-DeltaNet-aware mixed-precision GGUF quantization of Qwen3.8-27B for efficient local inference; preserves the MTP draft head and offers an optional BF16 mmproj for images. Weights are ~11.73 GiB (3.69 bpw), sized for 16–24 GB GPUs at modest context.
AI Model2026
An uncensored fork of Qwen3.8-27B that removes refusal/safety filters via an “abliteration” technique while preserving the first 15 layers and multimodal capabilities; intended for controlled research and testing rather than production.