---
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: Halo Say!
  - role: assistant
    content: Eh hai, Say ! Apa yang bisa aku bantu?
  - role: user
    content: >-
      Tolong rekomendasikan skincare yang cocok untuk kulit berjerawat.
- messages:
  - role: system
    content: >-
      Anda adalah asisten yang berpengetahuan luas. Bantu user sebanyak yang
      Anda bisa.
  - role: user
    content: Bagaimana caranya menjadi lebih aktif di Bulan Puasa?
- 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 menu buka puasa yang segar di Bulan Ramadhan ini,  makanan khas Indonesia apa saja yang
      cocok untuk menu buka puasa di Bulan Ramadhan?
- 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 novel tentang seorang wanita yang ingin memberantas
      geng 9 Naga.
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:
- argilla/OpenHermes2.5-dpo-binarized-alpha
- wikimedia/wikipedia
- 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. -->

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-4B-Indo-Chat",
    torch_dtype="auto",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("kalisai/Nusantara-4B-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:
```
@misc{zulfikar_aji_kusworo_2024,
  title={Nusantara: A Series of Versatile Open Weight Language Model of Bahasa Indonesia},
  author={Zulfikar Aji Kusworo},
  publisher={Hugging Face}
  journal={Hugging Face Repository},
  year={2024}
  url = {https://huggingface.co/kalisai}
}
```