This BF16 conversion of Qwen3-ASR-1.7B-hf runs with the main branch of ninfer-extended. Audio encoding, language prefill and decode run in the native C++/CUDA engine. The artifact includes the tokenizer, processor and chat template, with all 707 source parameters preserved byte for byte. Also included: a native BF16 Qwen3-ForcedAligner-0.6B artifact for word timestamps. See the combined ASR/alignment workflow and measurements below. On 60-second English audio, NInfer processes 62.5 seconds of audio per second on RTX 5070 Ti and 87.7 seconds per second on RTX 6000D. Four 30-second English recordings reach 197.8 and 299.0 audio seconds per second, respectively. Audio seconds/s = total input…
Independent publisher
ByronLee
ByronLeeee
Models in Library2
Datasets in Library0
Models on Hugging Face3
Followers—
Compare the published evidence
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: Image and text to text, Speech recognition.
Reported licenses: apache-2.0. 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
This BF16 conversion of Xiaomi-OCR-0 supports OCR and document parsing. The source model is based on Qwen3.5-0.8B-Base. The artifact includes language and vision weights, the tokenizer and image-processing configuration. Build the ninfer-extended main branch to run this artifact. This starts an OCR service with 32K context per request, four concurrent requests and BF16 weights/KV. Build dependencies: 64-bit Linux (WSL2 on Windows), CUDA supporting sm120a, C++20, CMake ≥3.28, Ninja, FFmpeg development libraries, libcurl, PCRE2, cuDNN 9 and cuBLAS. Omit CUBLASROOT when cuBLAS is installed with CUDA. Both engines use BF16 weights/KV, 4K context, one request, identical images/prompts, greedy…