A 3B-parameter causal LLM tuned for verifiable multi-step reasoning in math, coding and STEM using a Spectrum-to-Signal post-training pipeline (SFT, RL, offline self-distillation); not recommended for tool-calling/agent tasks.
Provides a locally runnable GGUF quantized build of Kimi K2.7 Code for multimodal, coding-focused agentic workflows — a 1T-parameter MoE model with 256K context, native int4 support, preserved thinking-mode, and image/video input support.
Provides an open-weight native multimodal agent that understands text and images within a 1,048,576-token context window for long-horizon coding, visual reasoning, and tool-driven workflows. Uses a 2.8T-parameter Mixture-of-Experts architecture (KDA + AttnRes) with MXFP4 quantization; best suited for research and large-scale inference setups.
Open-weights agentic coding model that layers Claude Fable‑5 tool‑use SFT onto a reasoning‑distilled Qwen3.6 base; emits <tool_use> XML for file edits, shell commands and reads when prompted as an agent. Designed for agentic coding workflows; AGPL‑3.0 licensed.
Provides a lightweight repository-exploration subagent for LLM coding agents: invoked on demand to run parallel read-only READ/GLOB/GREP calls and return compact file-path plus line-range citations so the main solver gets focused evidence instead of noisy reads.
Fine-tuned full checkpoint of the Qwen3.6-27B base that produces structured, trace-style assistant outputs for code, technical reasoning, and instruction-following. Packaged for local GGUF conversion and local inference; not a LoRA adapter and not validated for production use.
Provides a large language model optimized for long-horizon agentic tasks and end-to-end coding workflows — with a stable 1,000,000-token context, IndexShare sparse-attention and multi-level thinking-effort modes. MIT-licensed and designed for deployments that need sustained long-context reasoning and coding.
Uses Parallel Looped Transformers (PLT) to make loop count a practical knob for code models, finding two loops give the best test-time gains. Trains 7B models on 18T tokens and attributes saturation beyond two loops to a gain–cost tradeoff from positional mismatch.
Provides FP8-quantized weights of GLM-5.2 — a 744B long-context LLM tuned for sustained 1M-token engineering, coding and agentic workflows; compatible with vLLM, Transformers, SGLang and Ascend NPU deployments.
Provides GGUF-quantized GLM-5.2 builds for local text-generation with a solid 1M-token context, dynamic 1-/2-bit quant options, and Unsloth runtime integrations — targeted at long-horizon coding, reasoning and agent workflows. MIT licensed.
Transcribes Arabic speech to text using a CohereLabs-trained ASR model compatible with the Hugging Face Transformers pipeline. Provides safetensors weights, endpoint compatibility and a DOI-tagged release; suitable for Arabic transcription workflows but may require adaptation for diverse dialects or noisy audio.
Performs one-shot, long-horizon OCR and document parsing by using Reference Sliding Window Attention (R-SWA) to keep the decoder KV cache constant, enabling single-pass multi-page transcription; code, model weights and an accompanying arXiv report are provided.