Removes safety refusals from a Gemma 4 E4B–based model and publishes uncensored, locally runnable GGUF/safetensors variants while preserving all tensors and fixing prior corruption. Intended for red‑teaming and offline research; not recommended for production.
Open-weight multimodal 35B Qwen3.6 model in Hugging Face Transformers format that supports image/video/text inputs and native long contexts (262,144 tokens). Emphasizes agentic coding and preserved reasoning traces (thinking), uses an MoE-backed architecture and is designed for self-hosting with vLLM/SGLang/KTransformers; requires multi-GPU resources for production.
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).
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.
Clinical question-answering model for psychological support in obesity weight-management. Integrates UK Biobank population evidence to produce clinically interpretable, stigma-aware responses that help clinicians identify distress, prompt screening, and suggest appropriate referrals.
Drafts multiple tokens in parallel with a lightweight block-diffusion drafter to enable speculative decoding for faster LLM inference. Designed to pair with Qwen3.6-35B-A3B and reports up to ~2.9× throughput improvements on common benchmarks.
A healed 64-layer 'frankenmerge' that stacks two Qwen3.5-derived finetunes into an ~18B GGUF model for multilingual text generation, reasoning, and reliable code/frontend output. Healed with a 1000-step QLoRA to reduce layer-boundary artifacts and targeted to run on 12–16 GB GPUs.
Detects and masks personally identifiable information (PII) in text using a bidirectional token-classification model for high-throughput, on‑premises sanitization. Key traits: 1.5B parameters, 128k-token context, Apache 2.0 license, and tunable precision/recall operating points.
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.
Generates expressive, prompt-driven text-to-speech audio with optional 10-second voice cloning; prompts control speaker identity, emotion, pauses and nonverbal sounds. An IC‑LoRA fine-tune of LTX‑2.3 that applies an imperceptible Resemble Perth watermark.
GGUF quantized files for a Qwen3.6-35B checkpoint fine-tuned with Claude Opus 4.6-style chain-of-thought distillation to improve reasoning. Offers multiple llama.cpp-compatible quant options (Q4/Q5/Q6/Q8) for local text-generation inference.
Fine-tuned Qwen3.6-35B-A3B MoE that reproduces Claude Opus 4.7-style chain-of-thought with explicit <think>…</think> blocks. Offers sparse activation (256 experts, ~3B active params), 64k context, and GGUF builds for local inference; best for long, multi-step reasoning but may emit very long reasoning traces.