LocalTranslate_EN_RO

LocalTranslate EN -> RO

This is a English -> Romanian translation model trained by Mihai Popa (with the help of Kimi K2.6 Thinking)! It's based on BART, and it's a lot smaller than other models.

Why?

Because it's for my own future LocalTranslate project! Unlike Google Translate, this uses models (LTR files in the future) that you download and put on your device! And yes, it translates locally!

Notes

• Trained in just 22 minutes on Colab T4 GPU. 24M parameters and 92 MB in size!

Model Configurations

Training Configurations

Limitations

• Not Perfect: As with any other model, it's not 100% perfect and can generate incorrect translations!
• English-Only: It's for English -> Romanian translation (NOT vice-versa)!

Evaluation Results

Usage

Code is by Gemini 3 Flash/Kimi K2.6 Thinking (then some little modifications by myself):

from transformers import BartForConditionalGeneration, AutoTokenizer
import torch

# 1. Load from your Hugging Face Repo
model_id = "MihaiPopa-1/LocalTranslate_EN_RO"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = BartForConditionalGeneration.from_pretrained(
    model_id,
    torch_dtype=torch.float32, # Standard for CPU
    device_map="cpu"           # Forces CPU usage
)

# 2. Translate to Romanian
inputs = tokenizer("At your current usage level, this runtime may last up to 1 hour.", return_tensors="pt")
outputs = model.generate(
    **inputs,
    max_length=64,
    num_beams=2,
    early_stopping=True,
    forced_eos_token_id=tokenizer.eos_token_id,
)
translation = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(translation)

Data Used