Instructions to use Qwen/Qwen2.5-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Qwen/Qwen2.5-3B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="Qwen/Qwen2.5-3B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-3B-Instruct")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-3B-Instruct")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Qwen/Qwen2.5-3B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Qwen/Qwen2.5-3B-Instruct"
# 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/Qwen2.5-3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Qwen/Qwen2.5-3B-Instruct

SGLang

How to use Qwen/Qwen2.5-3B-Instruct 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/Qwen2.5-3B-Instruct" \
    --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/Qwen2.5-3B-Instruct",
		"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/Qwen2.5-3B-Instruct" \
        --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/Qwen2.5-3B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Qwen/Qwen2.5-3B-Instruct with Docker Model Runner:
```
docker model run hf.co/Qwen/Qwen2.5-3B-Instruct
```

Incorrect path_or_model_id

by officialtgmteam - opened Apr 3, 2025

Discussion

officialtgmteam

Apr 3, 2025

Hello, i have problem with run model on my pc, I want run it in offline mode, but it write me error when i run it... it say:

"Incorrect path_or_model_id: 'D:/Qwen--Qwen2.5-3B-Instruct/.cache/models--Qwen--Qwen2.5-3B-Instruct/snapshots/aa8e72537993ba99e69dfaafaafaafa59ed015b17504d1'. Please provide either the path to a local folder or the repo_id of a model on the Hub."

I have downloaded model in this folder, but it doesn't see it, or I don't know why it return this error. My code is here:

try:
from transformers import AutoTokenizer, AutoModelForCausalLM

            Path(self.qwen_cache_dir).mkdir(parents=True, exist_ok=True)

            pretrained_net = "Qwen/Qwen2.5-3B-Instruct"
            pretrained = [self.qwen_model_path](D:/Qwen--Qwen2.5-3B-Instruct/.cache/models--Qwen--Qwen2.5-3B-Instruct/snapshots/aa8e72537993ba99e69dfaafaafaafa59ed015b17504d1)
            model_name = "Qwen/Qwen2.5-3B-Instruct"
            self.local_model = "Qwen/Qwen2.5-3B-Instruct"
            device_map = "auto"
            torch_dtype = torch.float16

            try:
                self.tokenizer = AutoTokenizer.from_pretrained(pretrained, local_files_only=True, cache_dir=self.qwen_cache_dir)
                print('Tokenizer run.')
                
            except Exception as e:  # noqa: E722
                print(f'{e}')
                return
            
            try:
                self.model = AutoModelForCausalLM.from_pretrained(
                    pretrained=pretrained,
                    local_model_available=True,
                    torch_dtype=torch_dtype,
                    device_map=device_map,
                    local_files_only=True,
                    cache_dir=self.qwen_cache_dir
                )
                self.model.eval()
                print('Qwen run.')
                self.model_name = model_name
            except Exception as e:  # noqa: E722
                print(f'{e}')
                return

can you please help me how to run it without connection to internet? Thank you so much.

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