Whisper Bemba Stt Ggml Allquants
This is a repository of GGML quants for whisper-bemba-stt, for use with whisper.cpp.
Model source
- Kind
- Other
- File size
- 85.5–923 MB
- Base model
- AbelZimba/whisper-bemba-stt
- Version
- vRevision 1991188
- Updated
- Sep 27, 2026
- Downloads
- 0
- Source
- Hugging Face
Source description
Whisper-Bemba-STT quants
This is a repository of GGML quants for whisper-bemba-stt, for use with whisper.cpp.
If you are looking for a program to run this model with, then I would recommend EasyWhisper UI, as it is user-friendly, has a GUI, and will automate a lot of the hard stuff for you.
List of Quants
Clicking on a link will download the corresponding quant instantly.
| Link | Quant | Size | Notes |
|---|---|---|---|
| GGML | F32 | 968 MB | Likely overkill. |
| GGML | F16 | 488 MB | Performs better than Q8_0 for noisy audio and music. |
| GGML | Q8_0 | 264 MB | Sweet spot; superficial quality loss at nearly double the speed. |
| GGML | Q6_K | 207 MB | |
| GGML | Q5_K | 175 MB | |
| GGML | Q5_1 | 190 MB | |
| GGML | Q5_0 | 175 MB | Last "good" quant; anything below loses quality rapidly. |
| GGML | Q4_K | 145 MB | Might not have lost too much quality, but I'm not sure. |
| GGML | Q4_1 | 160 MB | |
| GGML | Q4_0 | 145 MB | |
| GGML | Q3_K | 114 MB | |
| GGML | Q2_K | 89.7 MB | Completely non-sensical outputs. |
Questions you may have
Why do the "K-quants" not work for me?
My guess is that your GPU might be too old to recognize them, considering that I have gotten the same error on my GTX 1080. If you would like to run them regardless, you can try switching to CPU inference.
Are the K-quants "S", "M", or "L"?
The quantizer I was using was not specific about this, so I do not know about this either.
What program did you use to make these quants?
I used whisper.cpp v1.9.1 on Windows x64, leveraging CUDA 12.4.0.
One or multiple of the quants are not working for me.
Open a new discussion in the community tab about this, and I will look into the issue.
Sources
1 source
Sources
1 sourceVerified Aug 30
Model artifacts
12 artifacts
Model artifacts
12 artifactsSource excerpts
2 excerpts
Source excerpts
2 excerpts--- base_model: - AbelZimba/whisper-bemba-stt pipeline_tag: automatic-speech-recognition tags: - whisper.cpp - ggml - whisper - audio - speech - voice --- # Whisper-Bemba-STT quants This is a repository of **GGML quants for [whisper-bemba-stt](https://huggingface.co/AbelZimba/whisper-bemba-stt)**, for use with [whisper.cpp](https://github.com/ggml-org/whisper.cpp). If you are looking for a program to run this model with, then I would recommend [EasyWhisper UI](https://github.com/mehtabmahir/easy-whisper-ui), as it is user-friendly, has a GUI, and will automate a lot of the hard stuff for you. ## List of Quants Clicking on a link will download the corresponding quant instantly. | Link | Quant | Size | Notes |:-----|:-----|--------:|:------| | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-f32.bin) | F32 | 968 MB | Likely overkill. | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-f16.bin) | F16 | 488 MB | Performs better than Q8_0 for noisy audio and music. | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q8_0.bin) | Q8_0 | 264 MB | Sweet spot; superficial quality loss at nearly double the speed. | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q6_k.bin) | Q6_K | 207 MB | | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q5_k.bin) | Q5_K | 175 MB | | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q5_1.bin) | Q5_1 | 190 MB | | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q5_0.bin) | Q5_0 | 175 MB | Last "good" quant; anything below loses quality rapidly. | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q4_k.bin) | Q4_K | 145 MB | *Might* not have lost too much quality, but I'm not sure. | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q4_1.bin) | Q4_1 | 160 MB | | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q4_0.bin) | Q4_0 | 145 MB | | | [GGML](https://huggingface.co/Pomni/whisper-bemba-stt-ggml-allquants/resolve/main/ggml-bemba-stt-q3_k.bin) |...
Source context: 0 downloads · 0 likes · Pipeline automatic-speech-recognition · Repo Pomni/whisper-bemba-stt-ggml-allquants
