
The aim is to compress the mT5-small model to leave only the Ukrainian language and some basic English.

Reproduced the similar result (but with another language) from [this](https://towardsdatascience.com/how-to-adapt-a-multilingual-t5-model-for-a-single-language-b9f94f3d9c90) medium article. 

Results: 
- 300M params -> 75M params (75%)
- 250K tokens -> 8900 tokens
- 1.1GB size model -> 0.3GB size model
{"language": ["uk", "en"], "tags": ["mt5"]}
transformers pytorch mt5 text2text-generation uk en autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #uk #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


The aim is to compress the mT5-small model to leave only the Ukrainian language and some basic English.

Reproduced the similar result (but with another language) from this medium article. 

Results: 
- 300M params -> 75M params (75%)
- 250K tokens -> 8900 tokens
- 1.1GB size model -> 0.3GB size model
TAGS
#transformers #pytorch #mt5 #text2text-generation #uk #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

passage: TAGS
#transformers #pytorch #mt5 #text2text-generation #uk #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
