--- title: "MOSS-Transcribe-Diarize-GGUF" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/916cd559-6186-4e1c-a0c9-2854d2aa8bc7" updated: "2026-11-13" --- # MOSS-Transcribe-Diarize-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns audio into timestamped transcripts with speaker labels in one pass. A GGUF conversion of a 0.9B model for CrispASR, for people who want meeting or interview transcripts on their own computer. MOSS-Transcribe-Diarize-GGUF is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by cstr ## About ### What it is This is a GGUF copy of OpenMOSS-Team's MOSS-Transcribe-Diarize, prepared by cstr for the CrispASR program. One 0.9B model does speech recognition, tells speakers apart and adds timestamps. You get a transcript where each line has a time range and a speaker label. It supports English and Chinese. ### Who it suits People who need written transcripts of recordings with the speakers marked, and who prefer to run the model locally. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Journalism | Reporters with interview recordings | Run the model over an audio file | Getting a transcript that shows which speaker said each line | | Business | Teams that record meetings | Transcribe a meeting file with a list of names and terms | Adding product and team names to the hotwords list | | Research | Researchers who collect spoken data | Convert recordings to timestamped text | Producing subtitle style output for later review | Skip it if you need a hosted transcription service, or if your audio is in a language other than English or Chinese. ### Where to use it It is built for CrispASR, a command line program, and the files download on Windows, macOS or Linux. - CrispASR: the program that loads the GGUF files - Windows, macOS or Linux: where you can fetch the files with Python - A terminal: where you run the transcription command | Use case | Who | What they get back | | --- | --- | --- | | Meeting transcripts | Teams | Text with times and speaker labels | | Interview notes | Journalists | A labelled transcript to check against the audio | | Subtitle files | Video editors | Timed text from a recording | ### How to set it up You need Python to download the files and CrispASR to run them. - Python with pip - CrispASR installed on your computer - Disk space for one model file, between about 1.2 GB and 1.7 GB 1. Install the Hugging Face hub library. 2. Download the model files. 3. Pick a file size and point CrispASR at it. ```sh pip install -U huggingface_hub hf download cstr/MOSS-Transcribe-Diarize-GGUF ``` The repository holds three sizes of the model. | File type | Size | What it is | | --- | --- | --- | | F16 | 1.7 GB | Full precision copy | | Q8\_0 | 1.4 GB | Smaller copy at 8 bits | | Q4\_K | 1.2 GB | Smallest copy at 4 bits, the one its author recommends | ### How to use it Run crispasr with the moss-diarize backend on an audio file. The first command lets the program pick the model file by itself. ```bash crispasr --backend moss-diarize -m auto -f audio.wav -osrt ``` To give it a list of words it should expect, such as names or product terms: ```bash crispasr --backend moss-diarize \ -m moss-transcribe-diarize-0.9b-q4_k.gguf \ -f meeting.wav \ --hotwords "MOSS,CrispASR" \ -osrt ``` | Tool | What it does | | --- | --- | | crispasr | Runs the transcription with the moss-diarize backend | | -m | Chooses the model file, or auto | | -f | Names the audio file to transcribe | | --hotwords | Passes a comma separated list of words to expect | ### Example You point CrispASR at a recording called meeting.wav, with the hotwords MOSS and CrispASR. It returns a transcript in which every line carries a start and end time and a speaker label such as Speaker 1 or Speaker 2. ### For newcomers and experts If you are new to this, record a short clip with two voices and run the first command on it. Check that the output names two speakers and that the times line up with the audio. If you know the field, the card describes a Whisper style audio encoder with a temporal merge and an adapter, feeding a Qwen3-0.6B decoder. The decoder writes timestamp and speaker tokens along with the text. This repository only converts the format and quantizes it, with no retraining. Audio file goes into CrispASR → Whisper style encoder reads the audio → Qwen3 decoder writes tokens → Timed, speaker labelled text comes out ### Good to know The authors state that this is a conversion only, so the original model decides what it can and cannot do. - License: Apache 2.0, the same as the base model - Cost to run: none named - Data it reaches: the audio files you point it at - Not for: new training, since no training or fine tuning was done here. Questions about training data go to the original authors ## README ````markdown # MOSS-Transcribe-Diarize-GGUF Turns audio into timestamped transcripts with speaker labels in one pass. A GGUF conversion of a 0.9B model for CrispASR, for people who want meeting or interview transcripts on their own computer. Made by cstr on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: This is a GGUF copy of OpenMOSS-Team's MOSS-Transcribe-Diarize, prepared by cstr for the CrispASR program. One 0.9B model does speech recognition, tells speakers apart and adds timestamps. You get a transcript where each line has a time range and a speaker label. It supports English and Chinese. Who it suits: People who need written transcripts of recordings with the speakers marked, and who prefer to run the model locally. ```table Industry | Who uses it | How they use it | Example Journalism | Reporters with interview recordings | Run the model over an audio file | Getting a transcript that shows which speaker said each line Business | Teams that record meetings | Transcribe a meeting file with a list of names and terms | Adding product and team names to the hotwords list Research | Researchers who collect spoken data | Convert recordings to timestamped text | Producing subtitle style output for later review ``` Skip it if you need a hosted transcription service, or if your audio is in a language other than English or Chinese. Where to use it: It is built for CrispASR, a command line program, and the files download on Windows, macOS or Linux. - CrispASR: the program that loads the GGUF files - Windows, macOS or Linux: where you can fetch the files with Python - A terminal: where you run the transcription command ```table Use case | Who | What they get back Meeting transcripts | Teams | Text with times and speaker labels Interview notes | Journalists | A labelled transcript to check against the audio Subtitle files | Video editors | Timed text from a recording ``` How to set it up: You need Python to download the files and CrispASR to run them. - Python with pip - CrispASR installed on your computer - Disk space for one model file, between about 1.2 GB and 1.7 GB 1. Install the Hugging Face hub library. 2. Download the model files. 3. Pick a file size and point CrispASR at it. ```sh pip install -U huggingface_hub hf download cstr/MOSS-Transcribe-Diarize-GGUF ``` The repository holds three sizes of the model. ```table File type | Size | What it is F16 | 1.7 GB | Full precision copy Q8_0 | 1.4 GB | Smaller copy at 8 bits Q4_K | 1.2 GB | Smallest copy at 4 bits, the one its author recommends ``` How to use it: Run crispasr with the moss-diarize backend on an audio file. The first command lets the program pick the model file by itself. ```bash crispasr --backend moss-diarize -m auto -f audio.wav -osrt ``` To give it a list of words it should expect, such as names or product terms: ```bash crispasr --backend moss-diarize \ -m moss-transcribe-diarize-0.9b-q4_k.gguf \ -f meeting.wav \ --hotwords "MOSS,CrispASR" \ -osrt ``` ```table Tool | What it does crispasr | Runs the transcription with the moss-diarize backend -m | Chooses the model file, or auto -f | Names the audio file to transcribe --hotwords | Passes a comma separated list of words to expect ``` Example: You point CrispASR at a recording called meeting.wav, with the hotwords MOSS and CrispASR. It returns a transcript in which every line carries a start and end time and a speaker label such as Speaker 1 or Speaker 2. For newcomers and experts: If you are new to this, record a short clip with two voices and run the first command on it. Check that the output names two speakers and that the times line up with the audio. If you know the field, the card describes a Whisper style audio encoder with a temporal merge and an adapter, feeding a Qwen3-0.6B decoder. The decoder writes timestamp and speaker tokens along with the text. This repository only converts the format and quantizes it, with no retraining. ```flow Audio file goes into CrispASR Whisper style encoder reads the audio Qwen3 decoder writes tokens Timed, speaker labelled text comes out ``` Good to know: The authors state that this is a conversion only, so the original model decides what it can and cannot do. - License: Apache 2.0, the same as the base model - Cost to run: none named - Data it reaches: the audio files you point it at - Not for: new training, since no training or fine tuning was done here. Questions about training data go to the original authors ## On Hugging Face, 13 November 2026 - Parameters: 909M - Weights: about 454 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 2,616 - Likes: 10 - License: apache-2.0 - Languages: en, zh - Based on: OpenMOSS-Team/MOSS-Transcribe-Diarize - Tags: gguf, speech-recognition, speaker-diarization, timestamps, crispasr, multilingual ## Links - Model: https://huggingface.co/cstr/MOSS-Transcribe-Diarize-GGUF - Files: https://huggingface.co/cstr/MOSS-Transcribe-Diarize-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download cstr/MOSS-Transcribe-Diarize-GGUF ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [cstr/MOSS-Transcribe-Diarize-GGUF on Hugging Face](https://huggingface.co/cstr/MOSS-Transcribe-Diarize-GGUF) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | MOSS-Transcribe-Diarize-GGUF (this page) | 2,616 | 10 | 909M | apache-2.0 | 2026-08-02 | | [Orukeet](https://mindket.com/p/01ec445a-061b-4b1f-a0e9-91cef756f183) | 35,262 | 110 | 627M | cc-by-sa-4.0 | 2026-11-11 | | [parakeet-ultra-gguf](https://mindket.com/p/0f756bf9-7825-4294-af8b-c884a8d3877d) | 1,375,499 | 8 | 627M | cc-by-4.0 | 2026-10-16 | | [GigaChat3.1-10B-A1.8B-GGUF](https://mindket.com/p/3e03c635-d97c-4ad9-9c9e-80af78adeb40) | 19,408 | 95 | 10.7B | mit | 2026-03-25 | | [Mega-ASR](https://mindket.com/p/ccfa46f6-d6b8-4451-9688-bc6e87354a6a) | 0 | 104 | — | apache-2.0 | 2026-06-09 | | [MOSS-Transcribe-Diarize](https://mindket.com/p/54596977-df9c-49a1-98ed-0a671e987045) | 121,031 | 520 | 909M | apache-2.0 | 2026-10-31 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-08-02 - First published: 2026-07-11 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open cstr/MOSS-Transcribe-Diarize-GGUF on Hugging Face](https://huggingface.co/cstr/MOSS-Transcribe-Diarize-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/916cd559-6186-4e1c-a0c9-2854d2aa8bc7) - [Its page on Mindket](https://mindket.com/p/916cd559-6186-4e1c-a0c9-2854d2aa8bc7)