Transformers
PyTorch
Persian
English
t5
text2text-generation
farsi/persian
text-generation-inference
Instructions to use alighasemi/fa-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alighasemi/fa-t5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alighasemi/fa-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("alighasemi/fa-t5-base") - Notebooks
- Google Colab
- Kaggle
This is a smaller version of the google/mt5-base model with only Farsi and some English embeddings left.
- The original model has 582M parameters, with 384M of them being input and output embeddings.
- After shrinking the
sentencepiecevocabulary from 250K to 30K (top 10K English and top 20K Russian tokens) the number of model parameters was reduced to 244M parameters, and the model size was reduced from 2.2GB to 0.9GB - 42% of the original one.
The creation of this model is described in the post How to adapt a multilingual T5 model for a single language along with the source code.
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