Instructions to use Qwen/Qwen3-30B-A3B-Instruct-2507 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Qwen/Qwen3-30B-A3B-Instruct-2507 with Transformers:

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

pipe = pipeline("text-generation", model="Qwen/Qwen3-30B-A3B-Instruct-2507")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-30B-A3B-Instruct-2507")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-30B-A3B-Instruct-2507", device_map="auto")
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/Qwen3-30B-A3B-Instruct-2507 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Qwen/Qwen3-30B-A3B-Instruct-2507"
# 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/Qwen3-30B-A3B-Instruct-2507",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Qwen/Qwen3-30B-A3B-Instruct-2507

SGLang

How to use Qwen/Qwen3-30B-A3B-Instruct-2507 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/Qwen3-30B-A3B-Instruct-2507" \
    --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/Qwen3-30B-A3B-Instruct-2507",
		"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/Qwen3-30B-A3B-Instruct-2507" \
        --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/Qwen3-30B-A3B-Instruct-2507",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Qwen/Qwen3-30B-A3B-Instruct-2507 with Docker Model Runner:
```
docker model run hf.co/Qwen/Qwen3-30B-A3B-Instruct-2507
```

关于 static KV-Cache(ValueError: This model does not support cache_implementation='static')

#11

by luohuashijieyoufengjun - opened Aug 6, 2025

Discussion

luohuashijieyoufengjun

Aug 6, 2025

•

edited Aug 6, 2025

使用unsloth框架对Qwen/Qwen3-30B-A3B-Instruct-2507进行lora微调之后，再进行推理，会报这个错：
ValueError: This model does not support cache_implementation='static'. Please check the following issue: huggingface/transformers#28981
经研究得知大概率是因为Qwen3 没有显式声明支持 static cache。想问一下官方有修复这个报错的打算吗？
下面是我的code：
model, tokenizer = FastLanguageModel.from_pretrained(
model_name = model_path,
max_seq_length = MAX_LENGTH,
load_in_4bit = True,
load_in_8bit = False,
full_finetuning = False, # lora微调这个改为False
dtype=torch.float16,
)

inputs = tokenizer("中国的首都是", return_tensors="pt").to(model.device)
out = model.generate(
**inputs,
max_new_tokens = 64,
do_sample = True,
cache_implementation = None # ← 手动关掉
)
print(tokenizer.decode(out[0], skip_special_tokens=True))

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