Optimized Q4KM GGUF quantization of NetEase Youdao Confucius4-R2T2, a low-latency, append-only streaming ASR model (fine-tuned from Qwen3-ASR-1.7B with Longest Stable Prefix decoding), ready for native execution in transcribe.cpp and audio.cpp. Previous GGUF releases were constrained to Q80 or higher because uniform 4-bit and 5-bit quantizations either suffered from catastrophic empty-output cliffs or exhibited silent language drift (e.g. flipping to English when transcribing German or Russian). This release introduces an asymmetric per-tensor quantization recipe that breaks through that barrier: For the full ablation study, complete empirical test tables across 20+ quantization arms…
Independent publisher
Dorian
Nairod785
Models in Library3
Datasets in Library0
Models on Hugging Face1
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Published tasks: Speech recognition.
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Models
GGUF quantizations of moondream/parakeet-ultra for transcribe.cpp. Parakeet Ultra is Moondream's full-precision post-training of NVIDIA's parakeet-tdt-0.6b-v3: the same FastConformer encoder (24 layers, dmodel 1024) and TDT transducer decoder, the same 25-language 8192-piece vocabulary, with better accuracy than v3 across English, European languages, noisy audio and long-form speech (upstream figures below). It takes 16 kHz mono audio and returns a punctuated, cased transcript with optional token/word timestamps. It is not a streaming model and does not translate. - How these files were made and how to reproduce them: QUANTIZATION.md Every file is at most the size of the parent checkpoint…
GGUF files of moondream/parakeet-redux for transcribe.cpp, keeping the model ternary: the encoder weights stay {−1, 0, +1} codes with one scale per 128 weights (1.75 bits/weight) and run on dedicated ternary kernels. Nothing is dequantized on disk. Parakeet Redux is Moondream's ternary sibling of parakeet-ultra, itself a post-training of NVIDIA's parakeet-tdt-0.6b-v3: FastConformer encoder + TDT transducer decoder, 25 European languages, 16 kHz mono input, punctuated and cased output with optional token/word timestamps. Not a streaming model; does not translate. - Format details, kernels, and how to reproduce: QUANTIZATION.md The ternary encoder weights (604 M, 1.75 bits/weight) are…