Instructions to use LINs-lab/DynMoE-StableLM-1.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LINs-lab/DynMoE-StableLM-1.6B with Transformers:

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

pipe = pipeline("text-generation", model="LINs-lab/DynMoE-StableLM-1.6B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("LINs-lab/DynMoE-StableLM-1.6B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use LINs-lab/DynMoE-StableLM-1.6B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LINs-lab/DynMoE-StableLM-1.6B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LINs-lab/DynMoE-StableLM-1.6B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LINs-lab/DynMoE-StableLM-1.6B

SGLang

How to use LINs-lab/DynMoE-StableLM-1.6B 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 "LINs-lab/DynMoE-StableLM-1.6B" \
    --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": "LINs-lab/DynMoE-StableLM-1.6B",
		"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 "LINs-lab/DynMoE-StableLM-1.6B" \
        --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": "LINs-lab/DynMoE-StableLM-1.6B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LINs-lab/DynMoE-StableLM-1.6B with Docker Model Runner:
```
docker model run hf.co/LINs-lab/DynMoE-StableLM-1.6B
```

Improve model card: Update pipeline tag, add library name, and update news section

by nielsr HF Staff - opened Mar 11, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+82

-29

nielsr

Mar 11, 2025

This PR improves the model card by:

Correcting the pipeline_tag to text-generation, which accurately reflects the model's functionality.
Adding the library_name tag as transformers for better model loading.
Updating the news section with the latest information from the Github README, including the ICLR 2025 acceptance.

These changes ensure the model card is more informative and facilitates easier model usage and discovery.

Improve model card: Update pipeline tag, add library name, and update news sectiondc5bca0e

kenshinn changed pull request status to merged Mar 24, 2025

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