metadata
library_name: transformers
tags:
- seq2seq
license: apache-2.0
datasets:
- Helsinki-NLP/europarl
- Helsinki-NLP/opus-100
language:
- en
- it
base_model:
- bigscience/mt0-small
pipeline_tag: translation
metrics:
- bleu
🍀 Quadrifoglio - A small model for English -> Italian translation
Quadrifoglio is an encoder-decoder transformer model for English-Italian text translation based on bigscience/mt0-small. It was trained on the en-it section of Helsinki-NLP/opus-100 and Helsinki-NLP/europarl.
Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
# Load model and tokenizer from checkpoint directory
tokenizer = AutoTokenizer.from_pretrained("LeonardPuettmann/mt0-Quadrifoglio-mt-en-it")
model = AutoModelForSeq2SeqLM.from_pretrained("LeonardPuettmann/mt0-Quadrifoglio-mt-en-it")
def generate_response(input_text):
input_ids = tokenizer("translate English to Italian:" + input_text, return_tensors="pt").input_ids
output = model.generate(input_ids, max_new_tokens=256)
return tokenizer.decode(output[0], skip_special_tokens=True)
text_to_translate = "I would like a cup of green tea, please."
response = generate_response(text_to_translate)
print(response)
Evaluation
Done on the Opus 100 test set.
BLEU
| mt0-Quadrifoglio | mt0-small | |
|---|---|---|
| BLEU Score | 0.3220 | 0.0159 |
| Precision 1 | 0.6168 | 0.2350 |
| Precision 2 | 0.3773 | 0.0290 |
| Precision 3 | 0.2601 | 0.0076 |
| Precision 4 | 0.1833 | 0.0013 |