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README.md
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license: apache-2.0
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---
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license: apache-2.0
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quantized_by: Pomni
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language:
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base_model:
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- openai/whisper-tiny
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pipeline_tag: automatic-speech-recognition
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tags:
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- whisper.cpp
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- ggml
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- whisper
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- audio
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- speech
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- voice
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---
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# Whisper-Tiny quants
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This is a repository of **GGML quants for [whisper-tiny](https://huggingface.co/openai/whisper-tiny)**, for use with [whisper.cpp](https://github.com/ggml-org/whisper.cpp).
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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.
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## List of Quants
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Not all of the links will work right now, as I am still in the middle of quantizing them. Clicking on a link will download the corresponding quant instantly.
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| Link | Quant | Size | Notes
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|:-----|:-----|--------:|:------|
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-f32.bin) | F32 | ? MB | Likely overkill. |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-f16.bin) | F16 | ? MB | Performs better than Q8_0 for noisy audio and music. |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q8_0.bin) | Q8_0 | ? MB | Sweet spot; superficial quality loss at nearly double the speed. |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q6_k.bin) | Q6_K | ? MB | |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q5_k.bin) | Q5_K | ? MB | |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q5_1.bin) | Q5_1 | ? MB | |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q5_0.bin) | Q5_0 | ? MB | Last "good" quant; anything below loses quality rapidly. |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q4_k.bin) | Q4_K | ? MB | *Might* not have lost too much quality, but I'm not sure. |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q4_1.bin) | Q4_1 | ? MB | |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q4_0.bin) | Q4_0 | ? MB | |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q3_k.bin) | Q3_K | ? MB | |
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| [GGML](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/resolve/main/ggml-tiny-q2_k.bin) | Q2_K | ? MB | Completely non-sensical outputs. |
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The F16 quant was taken from [ggerganov/whisper.cpp/ggml-tiny.bin](https://huggingface.co/ggerganov/whisper.cpp/blob/main/ggml-tiny.bin).
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## Questions you may have
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### Why do the "K-quants" not work for me?
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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.
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### Are the K-quants "S", "M", or "L"?
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The quantizer I was using was not specific about this, so I do not know about this either.
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### What program did you use to make these quants?
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I used [whisper.cpp v1.7.6](https://github.com/ggml-org/whisper.cpp/releases/tag/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.
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### One or multiple of the quants are not working for me.
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[Open a new discussion](https://huggingface.co/Pomni/whisper-tiny-ggml-allquants/discussions/new) in the community tab about this, and I will look into the issue.
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