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metadata
license: apache-2.0
quantized_by: Pomni
language:
  - en
base_model:
  - openai/whisper-medium.en
pipeline_tag: automatic-speech-recognition
tags:
  - whisper.cpp
  - ggml
  - whisper
  - audio
  - speech
  - voice

Whisper-Medium.en quants

This is a repository of GGML quants for whisper-medium.en, 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

Check the Files and versions tab for file sizes. Clicking on a link will download the corresponding quant instantly.

Link Quant Size Notes
GGML F32 ? MB Likely overkill.
GGML F16 ? MB Performs better than Q8_0 for noisy audio and music.
GGML Q8_0 ? MB Sweet spot; superficial quality loss at nearly double the speed.
GGML Q6_K ? MB
GGML Q5_K ? MB
GGML Q5_1 ? MB
GGML Q5_0 ? MB Last "good" quant; anything below loses quality rapidly.
GGML Q4_K ? MB Might not have lost too much quality, but I'm not sure.
GGML Q4_1 ? MB
GGML Q4_0 ? MB
GGML Q3_K ? MB
GGML Q2_K ? MB Completely non-sensical outputs.

The F16 quant was taken from ggerganov/whisper.cpp/ggml-medium.en.bin.

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 v1.7.6 on Windows x64, leveraging CUDA 12.4.0. For the F32 quant, I converted the original Hugging Face (H5) format model to a GGML using the models/convert-h5-to-ggml.py script.

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.