Independent publisher

Max Farrell

maxffarrell

Models in Library2

Datasets in Library0

Models on Hugging Face4

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This profile connects the 2 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: Audio to audio, Speech recognition.

Reported licenses: apache-2.0, mit. 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

Model · Speech recognition

ARK-ASR-0.6B-GGUF

Max Farrell

Community Q8 conversion of Edge0/ARK-ASR-0.6B, prepared for a draft Hex integration. No retraining. Not affiliated with the original authors, and not a canonical handy-computer artifact. Requires an ARK-enabled runtime. Stock llama.cpp, whisper.cpp and released transcribe-cpp 0.2.4 cannot load it. Use the candidate runtime at revision 19f301609c06126e5071d1de5acdd95c714eec05. ark-asr-0.6b-Q80.gguf: 1,372,881,664 bytes. SHA-256: ceca6bacd9cab3b52892de6703562aeeb62dc8a4b14aab0b020706637dd127dc. The 0.6B name describes the decoder; the full model also contains the audio encoder and adapter. Q8 linear weights, F16 tied embedding/output matrix and convolutions, F32 norms/biases/frontend tensors.…

Open weights apache-2.0

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Model · Audio to audio

gtcrn-coreai

Max Farrell

This release mirrors maxffarrell/gtcrn-coreai at source commit 5a5b0529f89c7146fc196f602ed2635adc681374. Choose DNS3 for general speech enhancement; VCTK-DEMAND is provided for matching that training corpus and reproducing related experiments. Download the complete repository, preserving the.aimodel bundle directories: For deployment you can download only exports/, LICENSE, and THIRDPARTYNOTICES.md using hf download --include. The numerical and latency results below were measured in August 2026 on the specified beta software stack; they have not been remeasured for newer releases. A reproducible, streaming Core AI conversion of GTCRN, the 48.2K-parameter speech-enhancement network…

Open weights mit

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