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---
language:
- jv
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
- sft
---
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document Title</title>
<style>
h1 {
font-size: 36px;
color: navy;
font-family: 'Tahoma';
text-align: center;
}
</style>
</head>
<body>
<h1> Open models for indigenous Indonesian languages</h1>
</body>
</html>
<center>
<img src="https://imgur.com/R91sZas.png" alt="Bakpia" width="500" height="250">
<p><em>Bakpia is a family of open language models capable of responding in Javanese language. Version one of Bakpia is the first generative Javanese LLM gain functional instruction performance using solely synthetic data.</em></p>
<p><em style="color: black; font-weight: bold;">Beta preview</em></p>
</center>
Bakpia V1 is a family of Javanese language models. It is fine-tuned from available open models using massive synthetic data for Krama Javanese, where the prompts are generated by GPT-4o and the responses are generated by Claude 3 Haiku.
This repository contains the fp16 version of Bakpia V1 1.5B.
| Version | Base Model | URL |
|---------|------------|-----|
| V1 0.5B | Qwen 2 0.5B Instruct | [fp16](huggingface.co/afrizalha/Bakpia-V1-0.5B-Javanese/) |
| V1 1.5B | Qwen 2 1.5B Instruct | [fp16](huggingface.co/afrizalha/Bakpia-V1-1.5B-Javanese/) |
| V1 9B | Gemma 2 9B Instruct | [fp16](huggingface.co/afrizalha/Bakpia-V1-9B-Javanese-fp16)/[4bit](huggingface.co/afrizalha/Bakpia-V1-9B-Javanese-4bit/) |
## Version 1.0
This is the first version of Bakpia.
✨ Training
- 36K input-output pairs
- 64/128 lora r/alpha
- Rank-stabilized lora
✨ Features
- Single-turn QA across various domains.
- Ngoko Javanese not currently supported.
## Use
```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("afrizalha/Bakpia-V1-1.5B-Javanese")
model = AutoModelForCausalLM.from_pretrained("afrizalha/Bakpia-V1-1.5B-Javanese")
template = """<|im_start|>system
<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
"""
input = template.format(prompt="Kados pundi kulo saged nyinaoni Basa Jawa kanthi sae?"
input = tokenizer([input], return_tensors = "pt").to("cuda")
outputs = model.generate(**input, max_new_tokens = 1024, temperature=.5, use_cache=False, do_sample=True)
print(tokenizer.batch_decode(outputs)[0])
```
## Acknowledgments
- **Developed by:** Afrizal Hasbi Azizy
- **License:** Apache-2.0 |