Instructions to use microsoft/GRIN-MoE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/GRIN-MoE with Transformers:

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

pipe = pipeline("text-generation", model="microsoft/GRIN-MoE", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import GRIN-MoE
model = GRIN-MoE.from_pretrained("microsoft/GRIN-MoE", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use microsoft/GRIN-MoE with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/microsoft/GRIN-MoE

SGLang

How to use microsoft/GRIN-MoE 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 "microsoft/GRIN-MoE" \
    --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": "microsoft/GRIN-MoE",
		"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 "microsoft/GRIN-MoE" \
        --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": "microsoft/GRIN-MoE",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use microsoft/GRIN-MoE with Docker Model Runner:
```
docker model run hf.co/microsoft/GRIN-MoE
```

LiyuanLucasLiu commited on Sep 18, 2024

Commit

0bb393e

1 Parent(s): 4d29616

add meta data

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README.md +16 -0

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@@ -1,3 +1,19 @@
 <h1 align="center">	&#128513; MoE</h1>
 <h4 align="center">GRIN: <em>GR</em>adient-<em>IN</em>formed MoE</h4>
 <p align="center">

+---
+license: mit
+license_link: https://github.com/microsoft/GRIN-MoE/tree/main/LICENSE
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- nlp
+- code
+widget:
+- messages:
+  - role: user
+    content: Sally (a girl) has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have?
+library_name: transformers
+---
 <h1 align="center">	&#128513; MoE</h1>
 <h4 align="center">GRIN: <em>GR</em>adient-<em>IN</em>formed MoE</h4>
 <p align="center">