Instructions to use OrionZheng/openmoe-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OrionZheng/openmoe-8b with Transformers:

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

pipe = pipeline("text-generation", model="OrionZheng/openmoe-8b", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("OrionZheng/openmoe-8b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("OrionZheng/openmoe-8b", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OrionZheng/openmoe-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OrionZheng/openmoe-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OrionZheng/openmoe-8b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/OrionZheng/openmoe-8b

SGLang

How to use OrionZheng/openmoe-8b 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 "OrionZheng/openmoe-8b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OrionZheng/openmoe-8b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "OrionZheng/openmoe-8b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OrionZheng/openmoe-8b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OrionZheng/openmoe-8b with Docker Model Runner:
```
docker model run hf.co/OrionZheng/openmoe-8b
```

error in modeling_openmoe.py

by xiaojia1086 - opened Jun 11, 2025

Discussion

xiaojia1086

Jun 11, 2025

from colossalai.moe.layers import SparseML
while
ModuleNotFoundError: No module named 'colossalai.moe.layers
and i didnt find "SparseMLP" in colossalai

OrionZheng

Owner Jun 11, 2025

Hi Xiaojia, thanks for the report! I believe this error stems from a recent change in the ColossalAI repository. Could you please try creating a virtual environment and installing an archived version of ColossalAI instead? Feel free to ping me if the error persists.

You might also find the Colab Demo helpful :)
https://colab.research.google.com/drive/1TbFT7ACuHbb7o2WAJn_KKmfvUzN9Z_Xs?authuser=1

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