Ollaya package of Contrastive-LM/CLM-v0.1-8B and Qwen/Qwen3-8B by Contrastive-LM (projection heads) and the Qwen team (Qwen3-8B encoder). Ollaya runs open decision models locally, the way Ollama runs LLMs: typed questions in, calibrated answers out, behind a TypeSafe-compatible API. This repository holds only the files Ollaya derives, with no weights. Each graph is an ONNX export of the original model whose weights reference the authors' own weight files by byte offset, so ollaya pull downloads the weights from the upstream repositories, unmodified and pinned to a commit, and verifies their sha256. Each tag has an fp32 graph, used on CPU and GPU. Each tag also has decision.json (sequence…
Organization
Ollaya
ollaya-dev
Compare the published evidence
This profile connects the 3 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.
Published tasks: Text classification.
Reported licenses: apache-2.0, other. Open a record to review its specific license and conditions.
Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.
Models
Ollaya package of amyrmahdy/decima-small and amyrmahdy/decima-base and amyrmahdy/decima-agent by A. M. Madani (amyrmahdy). Ollaya runs open decision models locally, the way Ollama runs LLMs: typed questions in, calibrated answers out, behind a TypeSafe-compatible API. This repository holds only the files Ollaya derives, with no weights. Each graph is an ONNX export of the original model whose weights reference the authors' own weight files by byte offset, so ollaya pull downloads the weights from the upstream repositories, unmodified and pinned to a commit, and verifies their sha256. Each tag has an fp32 graph, used on CPU and GPU. Each tag also has decision.json (sequence layout, special…
Ollaya package of LiquidAI/d1-3B-GGUF by Liquid AI. Ollaya runs open decision models locally, the way Ollama runs LLMs: typed questions in, calibrated answers out, behind a TypeSafe-compatible API. This repository holds only the files Ollaya derives, with no weights. The model is the authors' own GGUF file: ollaya pull downloads it from their repository, unmodified and pinned to a commit, verifies its sha256, and Ollaya runs it on llama.cpp. Each tag has decision.json (the prompt, the option labels Ollaya reads and llama.cpp's settings) and calibration.json (temperatures). A vision tag also pulls the vision projector the table names, unmodified from its author's repository, which reads the…