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---
library_name: transformers
tags:
- unsloth
- llama3
- indonesia
license: llama3
datasets:
- catinthebag/Tumpeng-1-Indonesian
language:
- id
inference: false
---
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<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document Title</title>
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h1 {
font-size: 36px;
color: navy;
font-family: 'Tahoma';
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<h1>Introducing the Kancil family of open models</h1>
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<center>
<img src="https://imgur.com/9nG5J1T.png" alt="Kancil" width="600" height="300">
<p><em>Kancil is a fine-tuned version of Llama 3 8B using synthetic QA dataset generated with Llama 3 70B. Version zero of Kancil is the first generative Indonesian LLM gain functional instruction performance using solely synthetic data.</em></p>
<p><strong><a href="https://colab.research.google.com/drive/1OOwb6bgFycOODHPcLaJtHk1ObcjG275C?usp=sharing" style="color: blue; font-family: Tahoma;">❕Go straight to the colab demo❕</a></strong></p>
<p><em style="color: black; font-weight: bold;">Beta preview</em></p>
</center>
Selamat datang!
I am ultra-overjoyed to introduce you... the 🦌 Kancil! It's a fine-tuned version of Llama 3 8B with the Tumpeng, an instruction dataset of 14.8 million words. Both the model and dataset is openly available in Huggingface.
📚 The dataset was synthetically generated from Llama 3 70B. A big problem with existing Indonesian instruction dataset is they're in reality not-very-good-translations of English datasets. Llama 3 70B can generate fluent Indonesian! (with minor caveats 😔)
🦚 This follows previous efforts for collection of open, fine-tuned Indonesian models, like Merak and Cendol. However, Kancil solely leverages synthetic data in a very creative way, which makes it a very unique contribution!
### Version 1.0
This is the second working prototype, Kancil V1.
✨ Training
- 2.2x Dataset word count
- 2x lora parameters
- Rank-stabilized lora
- 2x fun
✨ New features
- Multi-turn conversation (beta; optimized for curhat/personal advice 😂)
- Better text generation (full or outline writing; optimized for essays)
- QA from text (copy paste to prompt and ask a question about it)
- Making slogans
This model was fine-tuned with QLoRA using the amazing Unsloth framework! It was built on top of [unsloth/llama-3-8b-bnb-4bit](https://huggingface.co/unsloth/llama-3-8b-bnb-4bit) and subsequently merged with the adapter.
### Uses
This model is developed with research purposes for researchers or general AI hobbyists. However, it has one big application: You can have lots of fun with it!
### Out-of-Scope Use
This is a research preview model with minimal safety curation. Do not use this model for commercial or practical applications.
You are also not allowed to use this model without having fun.
### Getting started
As mentioned, this model was trained with Unsloth. Please use its code for better experience.
```
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
# Available versions
KancilV1 = "catinthebag/Kancil-V1-llama3-fp16"
# Load the model
tokenizer = AutoTokenizer.from_pretrained("catinthebag/Kancil-V1-llama3-fp16")
model = AutoModelForCausalLM.from_pretrained("catinthebag/Kancil-V1-llama3-fp16")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
```
```
# This model was trained on this specific prompt template. Changing it might lead to performance degradations.
prompt_template = """<|user|>
{prompt}
<|assistant|>
{response}"""
# Start generating!
inputs = tokenizer(
[
prompt_template.format(
prompt="""Bagaimana cara memberi tahu orang tua kalau saya ditolak universitas favorit saya?""",
response="",)
], return_tensors = "pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens = 600, temperature=.3, use_cache = True)
print(tokenizer.batch_decode(outputs)[0].replace('\\n', '\n'))
```
**Note:** There is an issue with the dataset where the newline characters are interpreted as literal strings. Very sorry about this! 😔 Please keep the .replace() method to fix newline errors.
### Acknowledgments
- **Developed by:** Afrizal Hasbi Azizy
- **License:** Llama 3 Community License Agreement |