metadata
license: cc-by-nc-4.0
language:
- en
- si
pipeline_tag: translation
datasets:
- zaanind/sinhala_englsih_parrel_corpus
- zaanind/sinhala_englsih_nmt
inference:
parameters:
src_lang: eng_Latn
tgt_lang: sin_Sinh
widget:
- text: you will receive a notification when your order is ready for pickup
example_title: example 1
- text: you will receive a response to your inquiry within 24 hours
example_title: example 2
- text: >-
i'm glad i could make it to your birthday event it was such a memorable
experience
example_title: example 3
What Is This?
It is a NLLB-200-600M model fine-tuned for translating between englih and sinhala languages
Training & Inference Codes - https://github.com/zaanind/NLLB-200-Sinhala
Try It
How to use the model:
1.Install necessary libraries
pip install requests sentencepiece transformers==4.33 sacremoses sacrebleu
2.Translate!
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
import torch
model_name = "zaanind/nllb-ensi-v1-tuning" #download model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
def dotranslate(text): #define function for generation
inputs = tokenizer(text, return_tensors="pt")
translated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.lang_code_to_id["sin_Sinh"])
out = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
return out
dotranslate("hello how are you?") #translate