README.md

---
library_name: transformers
widget:
- messages:
  - role: system
    content: Anda adalah seorang konselor karir. User akan memberi Anda seorang individu
       mencari bimbingan dalam kehidupan profesional mereka, dan tugas Anda adalah membantu
       mereka dalam menentukan karir apa yang paling cocok bagi mereka berdasarkan keterampilan mereka,
       minat, dan pengalaman. Anda juga harus melakukan penelitian terhadap berbagai hal tersebut
       pilihan yang tersedia, jelaskan tren pasar kerja di berbagai industri, Dan
       saran tentang kualifikasi mana yang akan bermanfaat untuk mengejar bidang tertentu.
  - role: user
    content: Hellow!
  - role: assistant
    content: Hai! Apa yang bisa saya bantu?
  - role: user
    content: Saya tertarik untuk mengembangkan karir di bidang rekayasa perangkat lunak. Apa
       Anda mau merekomendasikan saya untuk melakukannya?
- messages:
  - role: system
    content: Anda adalah asisten yang berpengetahuan luas. Bantu user sebanyak yang Anda bisa.
  - role: user
    content: Bagaimana caranya menjadi lebih sehat?
- messages:
  - role: system
    content: Anda adalah asisten yang membantu dan memberikan tanggapan yang cerdas.
  - role: user
    content: Haloooo Bund!
  - role: assistant
    content: Halo! Apa yang bisa saya bantu?
  - role: user
    content: Saya perlu membangun situs web sederhana. Di mana saya harus mulai belajar tentang pengembangan web?
- messages:
  - role: system
    content: Anda adalah asisten yang sangat kreatif. Pengguna akan memberi Anda tugas, yang harus Anda selesaikan dengan seluruh pengetahuan Anda.
  - role: user
    content: Tulis latar belakang cerita game RPG tentang penyihir dan naga di dunia fiksi ilmiah.
inference:
  parameters:
    max_new_tokens: 128
    penalty_alpha: 0.5
    top_k: 4
pipeline_tag: text-generation
tags:
- conversational
- convAI
license: apache-2.0
language:
- id
- en
datasets:
- FreedomIntelligence/evol-instruct-indonesian
---


![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/642b04e4ecec03b44649e318/6CCm81lqJ-i7aB38MtrAY.jpeg)



### Model Description

Nusantara is a series of Open Weight Language Model of Bahasa Indonesia (Indonesia language). Nusantara is based from Qwen1.5 Language Model, finetuned by domain specific of datasets. 
As Chat-implemented language model, Nusantara is capable to do Question-Answering and respond to instructions given in Bahasa Indonesia. 
Due to limited resources, only 0.8B, 1.8B, 2.7B, 4B and 7B models are available. If you're interested in funding this project for further development, specific usage, or larger parameters, please contact us.


- **Finetuned by:** [Kalis AI](https://huggingface.co/kalisai)
- **Funded by:** Self-funded
- **Model type:** transformer-based decoder-only language model
- **Language(s):** Bahasa Indonesia (id), English (en)
- **License:** Nusantara is licensed under Apache-2.0, but any usage of this model should comply with [Qwen License](https://huggingface.co/Qwen/Qwen1.5-4B/blob/main/LICENSE)
- **Finetuned from model:** [Qwen1.5-4B](https://huggingface.co/Qwen/Qwen1.5-4B/tree/main)

### Attentions!

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Due to certain circumstances, models with <4B parameters tend to hallucinate easily. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 
Because this model is also trained with uncensored datasets, there is the possibility of negative impacts arising from using this model. All kinds of impacts that arise as a result of using this model are entirely the responsibility of the user. The model maker is not responsible for any risks incurred.


## How to Get Started with the Model

Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained(
    "kalisai/Nusantara-0.8B-Indo-Chat",
    torch_dtype="auto",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("kalisai/Nusantara-0.8B-Indo-Chat")

prompt = "Berikan saya resep memasak nasi goreng yang lezat."
messages = [
    {"role": "system", "content": "Kamu adalah Nusantara, asisten AI yang pintar."},
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)

generated_ids = model.generate(
    model_inputs.input_ids,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
```


## Citation

If you use the Nusantara language model in your research or project, please cite it as:
```
@article{Nusantara,
  title={Nusantara: An Open Weight Language Model of Bahasa Indonesia},
  author={Zulfikar Aji Kusworo},
  publisher={Hugging Face}
  journal={Hugging Face Repository},
  year={2024}
}
```
```
@article{qwen,
  title={Qwen Technical Report},
  author={Jinze Bai and Shuai Bai and Yunfei Chu and Zeyu Cui and Kai Dang and Xiaodong Deng and Yang Fan and Wenbin Ge and Yu Han and Fei Huang and Binyuan Hui and Luo Ji and Mei Li and Junyang Lin and Runji Lin and Dayiheng Liu and Gao Liu and Chengqiang Lu and Keming Lu and Jianxin Ma and Rui Men and Xingzhang Ren and Xuancheng Ren and Chuanqi Tan and Sinan Tan and Jianhong Tu and Peng Wang and Shijie Wang and Wei Wang and Shengguang Wu and Benfeng Xu and Jin Xu and An Yang and Hao Yang and Jian Yang and Shusheng Yang and Yang Yao and Bowen Yu and Hongyi Yuan and Zheng Yuan and Jianwei Zhang and Xingxuan Zhang and Yichang Zhang and Zhenru Zhang and Chang Zhou and Jingren Zhou and Xiaohuan Zhou and Tianhang Zhu},
  journal={arXiv preprint arXiv:2309.16609},
  year={2023}
}
```