janisrebekahv/finetuned-colloquial-tamil

📌 Model Overview

This is a fine-tuned version of suriya7/English-to-Tamil, trained to produce colloquial Tamil translations instead of formal Tamil.

✅ Translates English → Colloquial Tamil
✅ Incorporates slang, informal speech, and real-world phrasing
✅ Useful for chatbots, conversational AI, and social media applications

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📜 Dataset

🔹 Custom Dataset Used for Fine-Tuning:
📂 janisrebekahv/colloquial_tamil
This dataset was specifically curated to train this model, improving its ability to translate English to Colloquial Tamil accurately.
This model was fine-tuned on a custom dataset, which includes:

1️⃣ jarvisvasu/english-to-colloquial-tamil – A publicly available dataset for informal Tamil translations.
2️⃣ YouTube Comments Dataset (Custom-Created) – Extracted using the YouTube API and manually converted to colloquial Tamil for authenticity.
3️⃣ ChatGPT-Generated Data – Additional colloquial Tamil phrases aligned with natural speech patterns.

📝 Total dataset size: 16,269 sentence pairs

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🔥 Example Usage

Load and test the model using Hugging Face Transformers:

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Load model and tokenizer
model_name = "janisrebekahv/finetuned-colloquial-tamil"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Function to translate text
def translate(text):
    inputs = tokenizer(text, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=128)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Example translations
test_sentences = [
    "This is so beautiful",
    "Bro, are you coming or not?",
    "My mom is gonna kill me if I don't reach home now!"
]

for sentence in test_sentences:
    print(f"English: {sentence}")
    print(f"Colloquial Tamil: {translate(sentence)}\n")