transformers pytorch llama text-generation code_generation sql th en dataset:AIAT/Pangpuriye-dataset dataset:AIAT/Pangpuriye-public_ThaiSum40k dataset:AIAT/Pangpuriye-generated_by_LLama3-codeLlama dataset:AIAT/Pangpuriye-public_alpaca-cleaned dataset:AIAT/Pangpuriye-generated_by_typhoon doi:10.57967/hf/2193 license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- AIAT/Pangpuriye-dataset
- AIAT/Pangpuriye-public_ThaiSum40k
- AIAT/Pangpuriye-generated_by_LLama3-codeLlama
- AIAT/Pangpuriye-public_alpaca-cleaned
- AIAT/Pangpuriye-generated_by_typhoon
language:
- th
- en
license: apache-2.0
metrics:
- accuracy
pipeline_tag: text-generation
tags:
- code_generation
- sql
---

# 🤖 [Super AI Engineer Development Program Season 4](https://superai.aiat.or.th/) - Pangpuriye Table-based Question Answering Model

![logo](https://huggingface.co/datasets/AIAT/Pangpuriye-generated_by_typhoon/resolve/main/logo/logo.png)

This model was fine-tuned from the original [OpenThaiGPT-1.0.1-7b](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-7b-chat). The model is set under Apache license 2.0. 

## Example inference using huggingface transformers.

The following code is an exmaple of how to inference our model.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer, LlamaTokenizer
import pandas as pd

def get_prediction(raw_prediction):
    if "[/INST]" in raw_prediction:
        index = raw_prediction.index("[/INST]")
        return raw_prediction[index + 7:]

    return raw_prediction

tokenizer = LlamaTokenizer.from_pretrained("AIAT/Pangpuriye-openthaigpt-1.0.0-7b-chat", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("AIAT/Pangpuriye-openthaigpt-1.0.0-7b-chat", trust_remote_code=True)

schema = """your SQL schema"""
query = "หาจำนวนลูกค้าที่เป็นเพศชาย"

prompt = f"""
    [INST] <<SYS>>
    You are a question answering assistant. Answer the question as truthful and helpful as possible คุณคือผู้ช่วยตอบคำถาม จงตอบคำถามอย่างถูกต้องและมีประโยชน์ที่สุด
    <</SYS>>
    {schema}### (sql extract) {query} [/INST]
"""

tokens = tokenizer(prompt, return_tensors="pt")
output = model.generate(tokens["input_ids"], max_new_tokens=20, eos_token_id=tokenizer.eos_token_id)
print(get_prediction(tokenizer.decode(output[0], skip_special_tokens=True)))
```

## Acknowledgements

The model collaborated by the members of Panguriye's house during the LLMs hackathon in Super AI Engineer Development Program Season 4. 

We thank the organizers of this hackathon, [OpenThaiGPT](https://openthaigpt.aieat.or.th/), [AIAT](https://aiat.or.th/), [NECTEC](https://www.nectec.or.th/en/) and [ThaiSC](https://thaisc.io/) for this challenging task and opportunity to be a part of developing Thai large language model.

## Citation Information

If our work is useful for future development, please cite our model as follows:

```
@misc {artificial_intelligence_association_of_thailand_2024,
	author       = { {Artificial Intelligence Association of Thailand} },
	title        = { Pangpuriye-openthaigpt-1.0.0-7b-chat (Revision 21f9a62) },
	year         = 2024,
	url          = { https://huggingface.co/AIAT/Pangpuriye-openthaigpt-1.0.0-7b-chat },
	doi          = { 10.57967/hf/2193 },
	publisher    = { Hugging Face }
}
```