Instructions to use openbmb/MiniCPM5-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openbmb/MiniCPM5-2B with Transformers:

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

pipe = pipeline("text-generation", model="openbmb/MiniCPM5-2B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("openbmb/MiniCPM5-2B")
model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM5-2B", 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 openbmb/MiniCPM5-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openbmb/MiniCPM5-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM5-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/openbmb/MiniCPM5-2B

SGLang

How to use openbmb/MiniCPM5-2B 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 "openbmb/MiniCPM5-2B" \
    --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": "openbmb/MiniCPM5-2B",
		"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 "openbmb/MiniCPM5-2B" \
        --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": "openbmb/MiniCPM5-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use openbmb/MiniCPM5-2B with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM5-2B
```

funmaker commited on 12 days ago

Commit

a063f08

1 Parent(s): 0e9c66d

add the LiteRT-LM version of MiniCPM5-2B

Browse files

Files changed (2) hide show

README-cn.md +1 -0
README.md +1 -0

README-cn.md CHANGED Viewed

@@ -161,6 +161,7 @@ datasets:
 - **[MiniCPM5-2B-MLX](https://huggingface.co/openbmb/MiniCPM5-2B-MLX)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-MLX) · MLX / 4bit，适用于 Apple Silicon
 - **[MiniCPM5-2B-GPTQ](https://huggingface.co/openbmb/MiniCPM5-2B-GPTQ)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-GPTQ) · GPTQ / 4bit 量化模型
 - **[MiniCPM5-2B-DSpark](https://huggingface.co/openbmb/MiniCPM5-2B-DSpark)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-DSpark) · DSpark 草稿模型，用于推理加速
 **MiniCPM5-1B**

 - **[MiniCPM5-2B-MLX](https://huggingface.co/openbmb/MiniCPM5-2B-MLX)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-MLX) · MLX / 4bit，适用于 Apple Silicon
 - **[MiniCPM5-2B-GPTQ](https://huggingface.co/openbmb/MiniCPM5-2B-GPTQ)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-GPTQ) · GPTQ / 4bit 量化模型
 - **[MiniCPM5-2B-DSpark](https://huggingface.co/openbmb/MiniCPM5-2B-DSpark)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-DSpark) · DSpark 草稿模型，用于推理加速
+- **[MiniCPM5-2B-LiteRT](https://huggingface.co/litert-community/MiniCPM5-2B)** · [ModelScope](https://www.modelscope.cn/models/litert-community/MiniCPM5-2B) · MiniCPM5-2B 的 LiteRT-LM 版本
 **MiniCPM5-1B**

README.md CHANGED Viewed

@@ -172,6 +172,7 @@ Use this directory to choose the model format that matches your runtime:
 - **[MiniCPM5-2B-MLX](https://huggingface.co/openbmb/MiniCPM5-2B-MLX)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-MLX) · MLX / 4bit for Apple Silicon
 - **[MiniCPM5-2B-GPTQ](https://huggingface.co/openbmb/MiniCPM5-2B-GPTQ)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-GPTQ) · GPTQ / 4bit quantized model
 - **[MiniCPM5-2B-DSpark](https://huggingface.co/openbmb/MiniCPM5-2B-DSpark)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-DSpark) · DSpark draft model for inference acceleration
 **MiniCPM5-1B**

 - **[MiniCPM5-2B-MLX](https://huggingface.co/openbmb/MiniCPM5-2B-MLX)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-MLX) · MLX / 4bit for Apple Silicon
 - **[MiniCPM5-2B-GPTQ](https://huggingface.co/openbmb/MiniCPM5-2B-GPTQ)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-GPTQ) · GPTQ / 4bit quantized model
 - **[MiniCPM5-2B-DSpark](https://huggingface.co/openbmb/MiniCPM5-2B-DSpark)** · [ModelScope](https://www.modelscope.cn/models/OpenBMB/MiniCPM5-2B-DSpark) · DSpark draft model for inference acceleration
+- **[MiniCPM5-2B-LiteRT](https://huggingface.co/litert-community/MiniCPM5-2B)** · [ModelScope](https://www.modelscope.cn/models/litert-community/MiniCPM5-2B) · the LiteRT-LM version of MiniCPM5-2B
 **MiniCPM5-1B**