Instructions to use Qwen/Qwen2.5-Coder-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Qwen/Qwen2.5-Coder-7B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="Qwen/Qwen2.5-Coder-7B-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-Coder-7B-Instruct")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-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
HuggingChat
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Qwen/Qwen2.5-Coder-7B-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-Coder-7B-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-Coder-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Qwen/Qwen2.5-Coder-7B-Instruct

SGLang

How to use Qwen/Qwen2.5-Coder-7B-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-Coder-7B-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-Coder-7B-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-Coder-7B-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-Coder-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Qwen/Qwen2.5-Coder-7B-Instruct with Docker Model Runner:
```
docker model run hf.co/Qwen/Qwen2.5-Coder-7B-Instruct
```

I periodically encounter infinite generations

#16

by hiauiarau - opened Nov 10, 2024

Discussion

hiauiarau

Nov 10, 2024

I periodically encounter infinite generations in Qwen 2.5 7B Coder with FP8 quantization when feeding long texts around 20+k characters into the context.

I'm looking at their configs:
https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct/blob/main/config.json
https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct/blob/main/generation_config.json
https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct/blob/main/tokenizer_config.json

In short, these three configs have completely confused me.

Hmm, I also found this: https://github.com/QwenLM/Qwen2.5-Coder
Important

We have updated both the special tokens and their corresponding token ids to maintain consistency with Qwen2.5. The new special tokens are as follows:
{
"<|fim_prefix|>": 151659,
"<|fim_middle|>": 151660,
"<|fim_suffix|>": 151661,
"<|fim_pad|>": 151662,
"<|repo_name|>": 151663,
"<|file_sep|>": 151664,
"<|im_start|>": 151644,
"<|im_end|>": 151645
}

How to properly modify config.json, generation_config.json, and tokenizer_config.json??

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