Fine-tuned on Tamil-language QA pairs covering 10 major Indian and Tamil Nadu government welfare schemes (PM-KISAN, Amma Unavagam, MGNREGS, Ayushman Bharat, etc.)

Training details

Base model: meta-llama/Meta-Llama-3-8B
Method: QLoRA — 4-bit NF4 + LoRA (r=16, alpha=32, all projections)
Framework: Unsloth + TRL SFTTrainer
Dataset: 270 train / 30 val (Tamil script, deduplicated)
ROUGE-L: 0.0000 | BERTScore F1: 0.7482
Training time: ~125 min on Colab T4

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained("MURUGAYESU/tamil-govt-scheme-llama3-8b", torch_dtype=torch.float16, device_map='auto')
tokenizer = AutoTokenizer.from_pretrained("MURUGAYESU/tamil-govt-scheme-llama3-8b")

prompt = '''### Instruction:
கீழே கொடுக்கப்பட்ட அரசு திட்டம் பற்றிய கேள்விக்கு தமிழில் விரிவான பதிலளிக்கவும்.

### Input:
PM-KISAN திட்டத்திற்கு யார் தகுதியானவர்கள்?

### Response:
'''
inputs = tokenizer(prompt, return_tensors='pt').to('cuda')
output = model.generate(**inputs, max_new_tokens=150, temperature=0.1, do_sample=True)
print(tokenizer.decode(output[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True))

Covered schemes

PM-KISAN, Amma Unavagam, MGNREGS, Pradhan Mantri Awas Yojana, Ayushman Bharat, Kisan Credit Card, Sukanya Samridhi, CM Solar Scheme TN, Mukhyamantri Kalaignar Scheme, National Scholarship Portal

Disclaimer

This model provides general educational information only. Always verify with official government portals (india.gov.in, tn.gov.in) before making any decisions.

MURUGAYESU/tamil-govt-scheme-Llama-3.2-1B

Tamil Government Scheme QA — Llama-3.2-1B-Instruct-bnb-4bit

Training details

Usage

Covered schemes

Disclaimer

MURUGAYESU/
tamil-govt-scheme-Llama-3.2-1B