cstr/MOSS-Transcribe-Diarize-GGUF overview
MOSS Transcribe Diarize 0.9B GGUF GGUF conversions of OpenMOSS Team/MOSS Transcribe Diarize https://huggingface.co/OpenMOSS Team/MOSS Transcribe Diarize for Cr…
Runs locally from ~16.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
Model README
---
license: apache-2.0
tags:
- asr
- speech-recognition
- speaker-diarization
- timestamps
- gguf
- crispasr
base_model: OpenMOSS-Team/MOSS-Transcribe-Diarize
language:
- en
- zh
- multilingual
---
MOSS-Transcribe-Diarize-0.9B GGUF
GGUF conversions of OpenMOSS-Team/MOSS-Transcribe-Diarize for CrispASR.
Joint ASR + speaker diarization + timestamps in a single 0.9B model. Produces timestamped, speaker-labelled transcripts in one pass.
Files
| File | Size | Description |
|------|------|-------------|
| moss-transcribe-diarize-0.9b-f16.gguf | 1.7 GB | Full precision (F16) |
| moss-transcribe-diarize-0.9b-q8_0.gguf | 1.4 GB | 8-bit quantized |
| moss-transcribe-diarize-0.9b-q4_k.gguf | 1.2 GB | 4-bit quantized (recommended) |
| diff-harness-ref/moss-diarize-ref.gguf | 9.5 MB | Diff harness reference (jfk.wav ground truth) |
Usage
crispasr --backend moss-diarize -m auto -f audio.wav -osrt
With hotwords:
crispasr --backend moss-diarize \
-m moss-transcribe-diarize-0.9b-q4_k.gguf \
-f meeting.wav \
--hotwords "MOSS,CrispASR" \
-osrt
Output Format
[00:00:00.320 --> 00:00:02.220] (Speaker 1) And so, my fellow Americans,
[00:00:03.020 --> 00:00:07.640] (Speaker 1) ask not what your country can do for you,
[00:00:08.110 --> 00:00:10.540] (Speaker 1) ask what you can do for your country.
[00:00:11.440 --> 00:00:15.580] (Speaker 2) And so, my fellow Americans, ask not...
Architecture
Stock Whisper encoder (24L, 80 mel, Conv1d) with 4x temporal merge, VQAdaptor, time markers every 5s, and Qwen3-0.6B LM decoder. Output: [timestamp][Sxx]text[timestamp] format with speaker labels.
Diff Harness
All 4 stages pass at cos=1.000 on both F32 and Q4_K:
| Stage | cos_min | max_abs |
|-------|---------|---------|
| mel_spectrogram | 1.000000 | 1.20e-04 |
| conv_stem_out | 1.000000 | 6.11e-05 |
| encoder_output | 1.000000 | 1.24e-04 |
| audio_embeds | 1.000000 | 1.35e-02 |
Conversion
python models/convert-moss-transcribe-diarize-to-gguf.py \
--input OpenMOSS-Team/MOSS-Transcribe-Diarize \
--output moss-transcribe-diarize-0.9b-f16.gguf
crispasr-quantize moss-transcribe-diarize-0.9b-f16.gguf \
moss-transcribe-diarize-0.9b-q4_k.gguf q4_k
License
Apache-2.0 (same as the base model).
Provenance and EU AI Act Art. 53 note
- Upstream model: OpenMOSS-Team/MOSS-Transcribe-Diarize — published by
OpenMOSS-Team. - Upstream licence:
apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not. - What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
- Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository. No training-content summary was found on the upstream model card at the time of writing; that documentation gap is upstream's and is not filled here.
- Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.
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