Instructions to use opsirygi/MiniCPM5-1B-IndoChat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use opsirygi/MiniCPM5-1B-IndoChat with Transformers:

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

pipe = pipeline("text-generation", model="opsirygi/MiniCPM5-1B-IndoChat")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("opsirygi/MiniCPM5-1B-IndoChat")
model = AutoModelForCausalLM.from_pretrained("opsirygi/MiniCPM5-1B-IndoChat", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use opsirygi/MiniCPM5-1B-IndoChat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "opsirygi/MiniCPM5-1B-IndoChat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "opsirygi/MiniCPM5-1B-IndoChat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/opsirygi/MiniCPM5-1B-IndoChat

SGLang

How to use opsirygi/MiniCPM5-1B-IndoChat 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 "opsirygi/MiniCPM5-1B-IndoChat" \
    --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": "opsirygi/MiniCPM5-1B-IndoChat",
		"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 "opsirygi/MiniCPM5-1B-IndoChat" \
        --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": "opsirygi/MiniCPM5-1B-IndoChat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use opsirygi/MiniCPM5-1B-IndoChat with Docker Model Runner:
```
docker model run hf.co/opsirygi/MiniCPM5-1B-IndoChat
```

MiniCPM5-1B-IndoChat / README.md

Commit History

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Commit History

docs: add Indonesian adaptation Note + language en/zh/id 34776e3 verified

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Update README.md 71bb5b9 verified

Update README.md ea6cce7 verified

Update README.md c665fa6 verified

Update README.md 26baac7 verified

Update README.md 8f34c09 verified

Unsloth Model Card 9441f8a verified

Update README.md 0ce3212 verified

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docs: add Indonesian adaptation Note + language en/zh/id

34776e3
verified

Unsloth Model Card

8d336aa
verified

Update README.md

71bb5b9
verified

Update README.md

ea6cce7
verified

Update README.md

c665fa6
verified

Update README.md

26baac7
verified

Update README.md

8f34c09
verified

Unsloth Model Card

9441f8a
verified

Update README.md

0ce3212
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