This is a smaller version of the [google/mt5-base](https://huggingface.co/google/mt5-base) model with only Spanish embeddings left. 
* The original model has 582M parameters, with 237M of them being input and output embeddings. 
* After shrinking the `sentencepiece` vocabulary from 250K to 25K (top 25K Spanish tokens) the number of model parameters reduced to 237M parameters, and model size reduced from 2.2GB to 0.9GB - 42% of the original one.

## Citing & Authors
- Datasets : [cleaned corpora](https://github.com/crscardellino/sbwce)
- Model : [google/mt5-base](https://huggingface.co/google/mt5-base)
- Reference: [cointegrated/rut5-base](https://huggingface.co/cointegrated/rut5-base)

{"language": ["es"], "license": "mit", "tags": ["spanish"]}
transformers pytorch t5 text2text-generation spanish es license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #spanish #es #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

This is a smaller version of the google/mt5-base model with only Spanish embeddings left. 
* The original model has 582M parameters, with 237M of them being input and output embeddings. 
* After shrinking the 'sentencepiece' vocabulary from 250K to 25K (top 25K Spanish tokens) the number of model parameters reduced to 237M parameters, and model size reduced from 2.2GB to 0.9GB - 42% of the original one.

## Citing & Authors
- Datasets : cleaned corpora
- Model : google/mt5-base
- Reference: cointegrated/rut5-base

## Citing & Authors
- Datasets : cleaned corpora
- Model : google/mt5-base
- Reference: cointegrated/rut5-base
TAGS
#transformers #pytorch #t5 #text2text-generation #spanish #es #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ## Citing & Authors
- Datasets : cleaned corpora
- Model : google/mt5-base
- Reference: cointegrated/rut5-base
passage: TAGS
#transformers #pytorch #t5 #text2text-generation #spanish #es #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
## Citing & Authors
- Datasets : cleaned corpora
- Model : google/mt5-base
- Reference: cointegrated/rut5-base