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.

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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 9B.

Version	Base Model	URL	Training
V1 0.5B	Qwen 2 0.5B Instruct	fp16	Epoch = 1, Batch = 16*8, lr = 5e-5, linear schedule
V1 1.5B	Qwen 2 1.5B Instruct	fp16	Epoch = 1, Batch = 16*8, lr = 5e-5, linear schedule
V1 9B	Gemma 2 9B Instruct	fp16/4bit	Batch size = 16*8, lr = 4e-5, linear schedule

Training data is accessible here.

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.

Generate with template

# Update transformers for Gemma 2 compatibility
!pip install -q git+https://github.com/huggingface/transformers.git

from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer

tokenizer = AutoTokenizer.from_pretrained("afrizalha/Bakpia-V1-9B-Javanese-fp16")
model = AutoModelForCausalLM.from_pretrained("afrizalha/Bakpia-V1-9B-Javanese-fp16")
model.to("cuda")

template = """<start_of_turn>user
{prompt}<end_of_turn>
<start_of_turn>model
"""

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, streamer= TextStreamer(tokenizer), temperature=.5, use_cache=True, do_sample=True)

Acknowledgments

Developed by: Afrizal Hasbi Azizy
License: Apache-2.0