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