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Model: AksaraLLM/Kiel-Pro-0.5B-v3
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---
language:
- id
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
base_model: Qwen/Qwen2-0.5B
tags:
- indonesian
- aksarallm
- qwen2
- continued-pretrain
---
# Kiel-Pro-0.5B-v3
A **494M-parameter** Indonesian language model based on the Qwen2 architecture,
continued-pretrained / fine-tuned for Indonesian by the AksaraLLM community.
This is the **smallest fully-working AksaraLLM model**: it loads cleanly via
`AutoModelForCausalLM`, includes its own tokenizer, and produces coherent
Indonesian text on standard prompts.
## Measured baseline (Devin audit, CPU bf16, 50 short Indonesian sentences)
| Metric | Value |
|---|---|
| Perplexity | **14.7** |
| English-stopword ratio in ID-prompted output | 0.8% |
| Indonesian-stopword ratio in ID-prompted output | 23.2% |
| Parameters | 494.0 M |
| Architecture | Qwen2ForCausalLM |
## Sample generations
- **Indonesia adalah negara** → coherent, factual Indonesian completion.
- **Resep nasi goreng yang enak adalah** → coherent recipe-style Indonesian.
## Quickstart
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tok = AutoTokenizer.from_pretrained("AksaraLLM/Kiel-Pro-0.5B-v3")
model = AutoModelForCausalLM.from_pretrained(
"AksaraLLM/Kiel-Pro-0.5B-v3",
torch_dtype=torch.bfloat16,
device_map="auto",
)
inp = tok("Indonesia adalah negara", return_tensors="pt").to(model.device)
print(tok.decode(model.generate(**inp, max_new_tokens=100, do_sample=True, top_p=0.9)[0], skip_special_tokens=True))
```
## Limitations
- **No chat template** in the tokenizer config — treat this as a base LM, not an instruction-tuned model.
- **Identity is uncalibrated** — the model is descended from Qwen2 and may identify itself as "Qwen" if asked. A short identity SFT pass would fix this.
- **Hallucinations** typical of a 0.5B-parameter model: factual claims should always be verified.
- **No production guardrails / RLHF**.
## Recommended downstream work
1. Identity SFT (50100 prompts) to teach the model to say "AksaraLLM Kiel-Pro".
2. Add a `chat_template` (Qwen2 ChatML) to `tokenizer_config.json`.
3. Run IndoNLU / IndoMMLU benchmarks for a publishable score.
## License
Apache 2.0
## Sample outputs (CPU inference, greedy, repeat_penalty=1.15)
Real generation captured during the Devin audit on 2026-05-02. Greedy decoding (`do_sample=False`) so these are reproducible.
### Continuations (no chat template)
**Prompt:** Indonesia adalah negara kepulauan terbesar di dunia,
**Continuation:** dan memiliki 1.347 pulau kecil yang disebut indah rindu (dari bahasa Jawa: rumput). Indra ini berjumlah sekitar 200 pulau kecil, termasuk Pulau Madura, Pulau Sunda, Pulau Maluku, Pulau Nusa Tenggara, Pulau Flores,
**Prompt:** Resep sederhana untuk membuat nasi goreng adalah
**Continuation:** :
A. 200 gram nasi, 150 ml air, 3 lembar daun jeruk nipis, dan 4 bawang putih.
B. 200 gram nasi, 150 ml air, 3 lembar daun jeruk nipis, dan 6 bawang putih.
C. 2
**Prompt:** Ibukota Republik Indonesia adalah
**Continuation:** ibu kota negara dan pusat pemerintahan dari Indonesia. Ibukotanya terletak di Sumatera Barat, Indonesia. Penduduknya berjumlah 2.354.069 jiwa (2010). Ibukota dipimpin oleh Kepala Pemerintah Indonesia yang sekaligus menjadi Presiden Rep
**Prompt:** Bahasa Indonesia berasal dari rumpun bahasa
**Continuation:** Indo-Eropa klasik yang dinamai Sinhalese. Dari sisi etimologi, kata "sinah" berarti "pohon", sedangkan "lese" berarti "menggambar". Kata ini muncul dalam bahasa Sinhala dan merupakan salah satu nama untuk pohon-pohon di daerah itu. Pohon tersebut adalah pohon le

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{
"model": "Kiel-Pro-0.5B-v3",
"base": "Qwen/Qwen2.5-0.5B",
"method": "LoRA SFT",
"loss": 2.1166
}

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{%- if tools %}
{{- '<|im_start|>system\n' }}
{%- if messages[0]['role'] == 'system' %}
{{- messages[0]['content'] }}
{%- else %}
{{- 'You are a helpful assistant.' }}
{%- endif %}
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
{%- else %}
{%- if messages[0]['role'] == 'system' %}
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
{%- else %}
{{- '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- for message in messages %}
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>' + message.role }}
{%- if message.content %}
{{- '\n' + message.content }}
{%- endif %}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '\n<tool_call>\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{{- tool_call.arguments | tojson }}
{{- '}\n</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{{- message.content }}
{{- '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}

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{
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"dtype": "float16",
"eos_token_id": 151643,
"hidden_act": "silu",
"hidden_size": 896,
"initializer_range": 0.02,
"intermediate_size": 4864,
"layer_types": [
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],
"max_position_embeddings": 32768,
"max_window_layers": 24,
"model_type": "qwen2",
"num_attention_heads": 14,
"num_hidden_layers": 24,
"num_key_value_heads": 2,
"pad_token_id": null,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 1000000.0,
"rope_type": "default"
},
"sliding_window": null,
"tie_word_embeddings": true,
"transformers_version": "5.0.0",
"use_cache": false,
"use_mrope": false,
"use_sliding_window": false,
"vocab_size": 151936
}

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{
"bos_token_id": 151643,
"eos_token_id": 151643,
"pad_token_id": 151643,
"do_sample": false,
"max_new_tokens": 512,
"repetition_penalty": 1.15,
"temperature": 0.7,
"top_p": 0.9,
"top_k": 40,
"transformers_version": "5.0.0"
}

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{
"add_prefix_space": false,
"backend": "tokenizers",
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"clean_up_tokenization_spaces": false,
"eos_token": "<|endoftext|>",
"errors": "replace",
"extra_special_tokens": [
"<|im_start|>",
"<|im_end|>",
"<|object_ref_start|>",
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