Multilingual Grammar Corrector using mT5-small Demo(I'll upload them in full in 2 weeks)

This is a fine-tuned mT5-small model for multilingual grammar correction in English 99%, Spanish 75%, French 70%, and Russian 80%. It was trained on synthetic and human-curated data to correct grammatical mistakes in short sentences.

✨ Example

Input:

She go to school yesterday.

Output:

She went to school yesterday.

🧠 Model Details

Architecture: mT5-small
Layers: 8
Heads: 6
Languages supported: English, Spanish, French, Russian
Tokenization: SentencePiece with special tokens <pad>, </s>, <unk>

📦 How to Use

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model = AutoModelForSeq2SeqLM.from_pretrained("your-username/Multilingual-Grammar-Corrector")
tokenizer = AutoTokenizer.from_pretrained("your-username/Multilingual-Grammar-Corrector")

input_text = "She go to school yesterday."
inputs = tokenizer(input_text, return_tensors="pt")

output = model.generate(**inputs, max_new_tokens=64)
corrected = tokenizer.decode(output[0], skip_special_tokens=True)

print(corrected)  # ➜ She went to school yesterday.