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Please check google/mt5-base model. This model is pruned version of mt5-base model to only work in Turkish and English. Also for methodology, you can check Russian version of mT5-base cointegrated/rut5-base.
Usage
You should import required libraries by:
from transformers import T5ForConditionalGeneration, T5Tokenizer
import torch
To load model:
model = T5ForConditionalGeneration.from_pretrained('bonur/t5-base-tr')
tokenizer = T5Tokenizer.from_pretrained('bonur/t5-base-tr')
To make inference with given text, you can use the following code:
inputs = tokenizer("Bu hafta hasta olduğum için <extra_id_0> gittim.", return_tensors='pt')
with torch.no_grad():
hypotheses = model.generate(
**inputs,
do_sample=True, top_p=0.95,
num_return_sequences=2,
repetition_penalty=2.75,
max_length=32,
)
for h in hypotheses:
print(tokenizer1.decode(h))
You can tune parameters for better result, and this model is ready to fine-tune in bilingual downstream tasks with English and Turkish.
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