Instructions to use Sandroeth/cali-0.1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Sandroeth/cali-0.1B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Sandroeth/cali-0.1B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Sandroeth/cali-0.1B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Sandroeth/cali-0.1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sandroeth/cali-0.1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sandroeth/cali-0.1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Sandroeth/cali-0.1B

SGLang

How to use Sandroeth/cali-0.1B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Sandroeth/cali-0.1B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sandroeth/cali-0.1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Sandroeth/cali-0.1B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sandroeth/cali-0.1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Sandroeth/cali-0.1B with Docker Model Runner:
```
docker model run hf.co/Sandroeth/cali-0.1B
```

CALI-99M

CALI (Computer Assistant Lightweight Intelligence) adalah model bahasa ringan eksperimental yang dilatih dari nol menggunakan dataset bahasa Indonesia dan Inggris dengan skala terbatas.

Model ini dibuat untuk eksperimen arsitektur transformer ringan, efisiensi model kecil, dan penelitian training language model menggunakan resource serta dataset terbatas.

Model ini BUKAN foundation model skala besar dan TIDAK dilatih menggunakan huge-scale internet dataset seperti model komersial modern.

Catatan Penting

Karena ukuran dataset relatif kecil, model dapat memiliki bias yang cukup kuat terhadap domain terakhir atau domain yang paling dominan saat proses pretraining. Fine-tuning, alignment, atau continued pretraining sangat disarankan tergantung tujuan penggunaan model.

Detail Model

Property	Value
Parameters	99M
Layers	11
Hidden Size	768
Attention Heads	4
KV Heads	1
Head Dimension	192
FFN Dimension	2304
Context Length	1024
Vocabulary Size	32000

Pretraining

Model dilatih dari nol menggunakan dataset yang dipilih dan difilter sesuai kebutuhan eksperimen model, bukan untuk mengejar ukuran dataset sebesar mungkin.

Dataset meliputi:

Teks bahasa Inggris
Teks bahasa Indonesia
Wikipedia
Berita
Dokumen umum
Kode program

Progress Training

Tokens	Step	Final Loss
250M	13,564	3.53
350M	18,989	3.53
450M	24,415	4.69
614M	33,356	2.71

Notes

Arsitektur eksperimental
Memerlukan custom inference implementation
Menggunakan Grouped-Query Attention (GQA)
Ditujukan untuk riset dan eksperimen

Citation

If you use or reference this model in your research or projects, please cite:

@article{cali2026,
  title        = {CALI 0.1B},
  author       = {Sandroeth},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/Sandroeth/cali-0.1B}

Author

Sandroeth

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Safetensors

Model size

0.1B params

Tensor type

F32