|
--- |
|
base_model: meta-llama/Meta-Llama-3-8B-Instruct |
|
library_name: peft |
|
datasets: |
|
- Telugu-LLM-Labs/urdu_alpaca_yahma_cleaned_filtered |
|
--- |
|
|
|
# MISHANM/Urdu_text_generation_Llama3_8B_instruct |
|
|
|
This model is fine-tuned for the Urdu language, capable of answering queries and translating text Between English and Urdu . It leverages advanced natural language processing techniques to provide accurate and context-aware responses. |
|
|
|
|
|
|
|
## Model Details |
|
1. Language: Urdu |
|
2. Tasks: Question Answering(Urdu to Urdu) , Translation (English to Urdu ) |
|
3. Base Model: meta-llama/Meta-Llama-3-8B-Instruct |
|
|
|
|
|
|
|
# Training Details |
|
|
|
The model is trained on approx 29K instruction samples. |
|
1. GPUs: 2*AMD Instinct™ MI210 Accelerators |
|
|
|
|
|
|
|
|
|
## Inference with HuggingFace |
|
```python3 |
|
|
|
import torch |
|
from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
|
# Load the fine-tuned model and tokenizer |
|
model_path = "MISHANM/Urdu_text_generation_Llama3_8B_instruct" |
|
|
|
model = AutoModelForCausalLM.from_pretrained(model_path,device_map="auto") |
|
|
|
tokenizer = AutoTokenizer.from_pretrained(model_path) |
|
|
|
# Function to generate text |
|
def generate_text(prompt, max_length=1000, temperature=0.9): |
|
# Format the prompt according to the chat template |
|
messages = [ |
|
{ |
|
"role": "system", |
|
"content": "You are a Urdu language expert and linguist, with same knowledge give response in Urdulanguage.", |
|
}, |
|
{"role": "user", "content": prompt} |
|
] |
|
|
|
# Apply the chat template |
|
formatted_prompt = f"<|system|>{messages[0]['content']}<|user|>{messages[1]['content']}<|assistant|>" |
|
|
|
# Tokenize and generate output |
|
inputs = tokenizer(formatted_prompt, return_tensors="pt") |
|
output = model.generate( |
|
**inputs, max_new_tokens=max_length, temperature=temperature, do_sample=True |
|
) |
|
return tokenizer.decode(output[0], skip_special_tokens=True) |
|
|
|
# Example usage |
|
prompt = """What is LLM .""" |
|
translated_text = generate_text(prompt) |
|
print(translated_text) |
|
|
|
|
|
|
|
``` |
|
|
|
## Citation Information |
|
``` |
|
@misc{MISHANM/Urdu_text_generation_Llama3_8B_instruct, |
|
author = {Mishan Maurya}, |
|
title = {Introducing Fine Tuned LLM for Urdu Language}, |
|
year = {2024}, |
|
publisher = {Hugging Face}, |
|
journal = {Hugging Face repository}, |
|
|
|
} |
|
``` |
|
|
|
|
|
- PEFT 0.12.0 |