Qwen2 is one of the top open LLMs. As of Jun 2024, Qwen1.5-110B-Chat is ranked higher than GPT-4-0613 on the LMSYS Chatbot Arena Leaderboard.
📰 Update (26 April 2024) - SkyPilot now also supports the Qwen1.5-110B model! It performs competitively with Llama-3-70B across a series of evaluations. Use serve-110b.yaml to serve the 110B model.
📰 Update (6 Jun 2024) - SkyPilot now also supports the Qwen2 model! It further improves the competitive model, Qwen1.5.
- Get the best GPU availability by utilizing multiple resources pools across multiple regions and clouds.
- Pay absolute minimum — SkyPilot picks the cheapest resources across regions and clouds. No managed solution markups.
- Scale up to multiple replicas across different locations and accelerators, all served with a single endpoint
- Everything stays in your cloud account (your VMs & buckets)
- Completely private - no one else sees your chat history
After installing SkyPilot, run your own Qwen model on vLLM with SkyPilot in 1-click:
- Start serving Qwen 110B on a single instance with any available GPU in the list specified in serve-110b.yaml with a vLLM powered OpenAI-compatible endpoint (You can also switch to serve-72b.yaml or serve-7b.yaml for a smaller model):
sky launch -c qwen serve-110b.yaml
- Send a request to the endpoint for completion:
IP=$(sky status --ip qwen)
curl http://$IP:8000/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "Qwen/Qwen1.5-110B-Chat",
"prompt": "My favorite food is",
"max_tokens": 512
}' | jq -r '.choices[0].text'
- Send a request for chat completion:
curl http://$IP:8000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "Qwen/Qwen1.5-110B-Chat",
"messages": [
{
"role": "system",
"content": "You are a helpful and honest chat expert."
},
{
"role": "user",
"content": "What is the best food?"
}
],
"max_tokens": 512
}' | jq -r '.choices[0].message.content'
- With SkyPilot Serving, a serving library built on top of SkyPilot, scaling up the Qwen service is as simple as running:
sky serve up -n qwen ./serve-72b.yaml
This will start the service with multiple replicas on the cheapest available locations and accelerators. SkyServe will automatically manage the replicas, monitor their health, autoscale based on load, and restart them when needed.
A single endpoint will be returned and any request sent to the endpoint will be routed to the ready replicas.
- To check the status of the service, run:
sky serve status qwen
After a while, you will see the following output:
Services
NAME VERSION UPTIME STATUS REPLICAS ENDPOINT
Qwen 1 - READY 2/2 3.85.107.228:30002
Service Replicas
SERVICE_NAME ID VERSION IP LAUNCHED RESOURCES STATUS REGION
Qwen 1 1 - 2 mins ago 1x Azure({'A100-80GB': 8}) READY eastus
Qwen 2 1 - 2 mins ago 1x GCP({'L4': 8}) READY us-east4-a
As shown, the service is now backed by 2 replicas, one on Azure and one on GCP, and the accelerator type is chosen to be the cheapest available one on the clouds. That said, it maximizes the availability of the service while minimizing the cost.
- To access the model, we use a
curl
command to send the request to the endpoint:
ENDPOINT=$(sky serve status --endpoint qwen)
curl http://$ENDPOINT/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "Qwen/Qwen2-72B-Instruct",
"messages": [
{
"role": "system",
"content": "You are a helpful and honest code assistant expert in Python."
},
{
"role": "user",
"content": "Show me the python code for quick sorting a list of integers."
}
],
"max_tokens": 512
}' | jq -r '.choices[0].message.content'
It is also possible to access the Qwen service with a GUI using vLLM.
- Start the chat web UI (change the
--env
flag to the model you are running):
sky launch -c qwen-gui ./gui.yaml --env MODEL_NAME='Qwen/Qwen2-72B-Instruct' --env ENDPOINT=$(sky serve status --endpoint qwen)
- Then, we can access the GUI at the returned gradio link:
| INFO | stdout | Running on public URL: https://6141e84201ce0bb4ed.gradio.live