---
license: apache-2.0
language:
- ru
library_name: transformers
pipeline_tag: automatic-speech-recognition
tags:
- asr
- Pytorch
- pruned
- audio
- automatic-speech-recognition
---

# Whisper-small-ru-pruned

## Model info
This is a pruned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) model with only russian tokens left.
Pruning was made without any fine-tuning. Method from [this post](https://medium.com/m/global-identity-2?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Fhow-to-adapt-a-multilingual-t5-model-for-a-single-language-b9f94f3d9c90) was used.

## Size
Only 10% tokens was left including special whisper tokens, added whisper tokens, 100 most popular tokens from tokenizer and 3000 most popular Russian tokens computed by tokenization of russian text corpus.

Model size is 15%  less then original whisper-small:
|  | openai/whisper-small | waveletdeboshir/whisper-small-ru-pruned |
| :------ | :------ | :------ |
| n of parameters | 242 M | 205 M |
| n of parameters (with proj_out layer) | 281 M | 209 M |
| model file size | 967 Mb | 837 Mb |
| vocab_size | 51865 | 4705 |

## Other pruned whisper models
* [waveletdeboshir/whisper-tiny-ru-pruned](https://huggingface.co/waveletdeboshir/whisper-tiny-ru-pruned)
* [waveletdeboshir/whisper-base-ru-pruned](https://huggingface.co/waveletdeboshir/whisper-base-ru-pruned)

## Metrics
TODO

You can fine-tune this model on your data to achive better performance.

## Colab for pruning
TODO