metadata
datasets:
- nhuvo/MedEV
language:
- vi
- en
metrics:
- bleu
base_model:
- facebook/mbart-large-50
pipeline_tag: translation
library_name: transformers
tags:
- medical
- medical-machine-translation
How to use:
For fine-tuning
Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("trieutm/mbart-large-50-many-to-many-mmt-finetuned-vi-to-en")
model = AutoModelForSeq2SeqLM.from_pretrained("trieutm/mbart-large-50-many-to-many-mmt-finetuned-vi-to-en")
For inference
Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("translation", model="trieutm/mbart-large-50-many-to-many-mmt-finetuned-vi-to-en")