Instructions to use Qwen/CodeQwen1.5-7B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Qwen/CodeQwen1.5-7B-Chat with Transformers:

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

pipe = pipeline("text-generation", model="Qwen/CodeQwen1.5-7B-Chat")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Qwen/CodeQwen1.5-7B-Chat")
model = AutoModelForCausalLM.from_pretrained("Qwen/CodeQwen1.5-7B-Chat")
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/CodeQwen1.5-7B-Chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Qwen/CodeQwen1.5-7B-Chat"
# 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/CodeQwen1.5-7B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Qwen/CodeQwen1.5-7B-Chat

SGLang

How to use Qwen/CodeQwen1.5-7B-Chat 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/CodeQwen1.5-7B-Chat" \
    --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/CodeQwen1.5-7B-Chat",
		"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/CodeQwen1.5-7B-Chat" \
        --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/CodeQwen1.5-7B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Qwen/CodeQwen1.5-7B-Chat with Docker Model Runner:
```
docker model run hf.co/Qwen/CodeQwen1.5-7B-Chat
```

EXL2 Quants are up

by Dracones - opened Apr 16, 2024

Discussion

Dracones

Apr 16, 2024

Very nice model for its size. EXL2 quants are up with perplexity scoring so people can get an idea of size vs loss: https://huggingface.co/collections/Dracones/codeqwen15-7b-chat-661ed39a0325c1978192dba1

huybery

Apr 19, 2024

Thanks for your contribution!

sm54

May 22, 2024

Very nice model for its size. EXL2 quants are up with perplexity scoring so people can get an idea of size vs loss: https://huggingface.co/collections/Dracones/codeqwen15-7b-chat-661ed39a0325c1978192dba1

I downloaded the 8_0 quant and it gives me an error when trying to load it up in text-generation-webui. Something to do with a missing pre tokeniser Whitespace()? At least from my searches on the internet this seems to be the problem, although I don't know how to fix it.

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