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.