Instructions to use Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4 with Transformers:

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

pipe = pipeline("text-generation", model="Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4

SGLang

How to use Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4 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 "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4" \
    --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": "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4",
		"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 "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4" \
        --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": "Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4 with Docker Model Runner:
```
docker model run hf.co/Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4
```

Not working with sample code

by rupeshs - opened Mar 30, 2024

Discussion

rupeshs

Mar 30, 2024

Getting error
ValueError: The checkpoint you are trying to load has model type qwen2_moe but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date

rupeshs changed discussion status to closed Mar 30, 2024

bloomedout

Apr 4, 2024

Did you figure out how to fix this I can't get it to run in collab at all from this error.

bloomedout

Apr 4, 2024

•

edited Apr 4, 2024

To make this work in google colab you can use a gpu runtime then run these commands in a block then run example code.
!git clone https://github.com/huggingface/transformers.git
%cd transformers
!pip install optimum
!pip install auto-gptq
!pip install -e .
Then restart runtime to use packages installed then use the example code. Hopefully this helps anyone trying to use this model in colab as just installing transformers from source didn't matter as these dependencies had to be installed in this order for it to work on my instance.

rupeshs

Apr 5, 2024

•

edited Apr 5, 2024

Did you figure out how to fix this I can't get it to run in collab at all from this error.

I was checking it locally, I installed transformers from the source(git) and it worked!

rupeshs changed discussion status to open Apr 5, 2024

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