Instructions to use openbmb/MiniCPM-2B-dpo-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openbmb/MiniCPM-2B-dpo-bf16 with Transformers:

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

pipe = pipeline("text-generation", model="openbmb/MiniCPM-2B-dpo-bf16", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM-2B-dpo-bf16", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use openbmb/MiniCPM-2B-dpo-bf16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openbmb/MiniCPM-2B-dpo-bf16"
# 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/MiniCPM-2B-dpo-bf16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/openbmb/MiniCPM-2B-dpo-bf16

SGLang

How to use openbmb/MiniCPM-2B-dpo-bf16 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/MiniCPM-2B-dpo-bf16" \
    --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/MiniCPM-2B-dpo-bf16",
		"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/MiniCPM-2B-dpo-bf16" \
        --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/MiniCPM-2B-dpo-bf16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use openbmb/MiniCPM-2B-dpo-bf16 with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM-2B-dpo-bf16
```

Run MiniCPM-2B on CPU

by J22 - opened Feb 6, 2024

Discussion

J22

Feb 6, 2024

https://github.com/foldl/chatllm.cpp

    ________          __  __    __    __  ___ 
   / ____/ /_  ____ _/ /_/ /   / /   /  |/  /_________  ____  
  / /   / __ \/ __ `/ __/ /   / /   / /|_/ // ___/ __ \/ __ \ 
 / /___/ / / / /_/ / /_/ /___/ /___/ /  / // /__/ /_/ / /_/ / 
 \____/_/ /_/\__,_/\__/_____/_____/_/  /_(_)___/ .___/ .___/  
You are served by MiniCPM,                    /_/   /_/       
with 2724880896 (2.7B) parameters.

You  > 山东省最高的山是哪座山, 它比黄山高还是矮？差距多少？
A.I. >  山东省最高的山是泰山，位于山东省泰安市。泰山海拔1545米，是中国五岳之一，也是山东省最高峰。

黄山位于安徽省黄山市，是中国五岳之一，海拔1864米。从海拔上来看，泰山比黄山低，黄山比泰山高。黄山比泰山高约319米。