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

Libraries

How to use MegaScience/Qwen3-30B-A3B-MegaScience with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MegaScience/Qwen3-30B-A3B-MegaScience")
model = AutoModelForCausalLM.from_pretrained("MegaScience/Qwen3-30B-A3B-MegaScience")
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

vLLM

How to use MegaScience/Qwen3-30B-A3B-MegaScience with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MegaScience/Qwen3-30B-A3B-MegaScience"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MegaScience/Qwen3-30B-A3B-MegaScience",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/MegaScience/Qwen3-30B-A3B-MegaScience

SGLang

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

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

Improve model card: Add library name, abstract, GitHub link, and sample usage

by nielsr HF Staff - opened Jul 24, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

+52

-4

nielsr

Jul 24, 2025

This PR enhances the model card for MegaScience/Qwen3-30B-A3B-MegaScience by:

Adding library_name: transformers to the metadata, which enables the "Use in Transformers" widget on the model page for easier interaction.
Including the full paper abstract to provide immediate context about the model and its underlying research.
Adding direct links to the primary GitHub repository for the MegaScience project and its associated evaluation system, where users can find the data curation pipeline, evaluation details, and other resources.
Providing a practical Python code snippet for text generation using the transformers library, making it straightforward for users to get started with the model.

These updates aim to make the model card more comprehensive and user-friendly.

Improve model card: Add library name, abstract, GitHub link, and sample usagefaa228a0

Vfrz changed pull request status to merged Jul 24, 2025

Vfrz

MegaScience org Jul 24, 2025

Thank you very much for your effort in refining the README.

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