---
license: apache-2.0
language:
- en
base_model:
- MahmoudAshraf/acft-whisper-large-v3-turbo
base_model_relation: quantized
pipeline_tag: automatic-speech-recognition
---
# Model Card

## Model Description

This is a whisper.cpp quantization of the [FUTO acft](https://huggingface.co/collections/futo-org/whisper-acft-667c430f8de3a22b73151d74) whisper [large-v3-turbo finetune](https://huggingface.co/MahmoudAshraf/acft-whisper-large-v3-turbo/tree/main) performed by [MahmoudAshraf](https://huggingface.co/MahmoudAshraf/). series of [OpenAI's Whisper models](https://github.com/openai/whisper).

FUTO acft models have been finetuned for dynamic audio context robustness, allowing shorter audio contexts for better performance with short audio inputs. The method is detailed [in our GitHub repo](https://github.com/futo-org/whisper-acft).

- **License:** Apache-2.0
- **Finetuned from model:** OpenAI Whisper

## Quantization Process

The original `.safetensor` model was converted to ggml format and then quantized using tools provided with the [whisper.cpp](https://github.com/ggerganov/whisper.cpp) repo.

```shell
>conda activate whisper.cpp

> WHISPERCPP_REPO=~/whisper.cpp
> WHISPER_PACKAGE=~/python-packages # Location of pip `whisper` package
> python "$WHISPERCPP_REPO/models/convert-h5-to-ggml.py" ~/hf-models/acft-whisper-large-v3-turbo "$WHISPER_PACKAGE" ~/quantized-models/acft-whisper-large-v3-turbo_q8_0

> cd ~/quantized-models/acft-whisper-large-v3-turbo_q8_0
> mv ggml-model.bin acft-whisper-large-v3-turbo-f16.bin

> python "$WHISPERCPP_REPO/bin/quantize.exe" acft-whisper-large-v3-turbo-f16.bin acft-whisper-large-v3-turbo-q8_0.bin q8_0
ggml_common_quantize_0: model size  =  3085.62 MB
ggml_common_quantize_0: quant size  =   833.08 MB | ftype = 7 (q8_0)
main: quantize time = 20616.65 ms
main:    total time = 20616.65 ms
```

## Uses

These models are not useful by themselves under default Whisper runtime configurations.

The easiest way to test differing audio context is to use whisper.cpp with the `--audio-context` parameter. We provide converted whisper.cpp models in our [GitHub README](https://github.com/futo-org/whisper-acft?tab=readme-ov-file#finetuning-whisper-for-dynamic-audio-context-robustness).

## Other Information

More information can be found in this [GitHub README](https://github.com/futo-org/whisper-acft?tab=readme-ov-file#finetuning-whisper-for-dynamic-audio-context-robustness).