Instructions to use qihoo360/Light-R1-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use qihoo360/Light-R1-32B with Transformers:

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

pipe = pipeline("text-generation", model="qihoo360/Light-R1-32B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("qihoo360/Light-R1-32B")
model = AutoModelForCausalLM.from_pretrained("qihoo360/Light-R1-32B")
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 qihoo360/Light-R1-32B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "qihoo360/Light-R1-32B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "qihoo360/Light-R1-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/qihoo360/Light-R1-32B

SGLang

How to use qihoo360/Light-R1-32B 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 "qihoo360/Light-R1-32B" \
    --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": "qihoo360/Light-R1-32B",
		"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 "qihoo360/Light-R1-32B" \
        --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": "qihoo360/Light-R1-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use qihoo360/Light-R1-32B with Docker Model Runner:
```
docker model run hf.co/qihoo360/Light-R1-32B
```

Add metadata and correct paper link

by nielsr HF Staff - opened Mar 15, 2025

base: refs/heads/main

←

from: refs/pr/4

Discussion Files changed

-3

Files changed (1) hide show

README.md +6 -3

README.md CHANGED Viewed

@@ -1,13 +1,16 @@
 ---
-license: apache-2.0
 base_model:
 - Qwen/Qwen2.5-32B-Instruct
 ---
 # Light-R1: Surpassing R1-Distill from Scratch\* with \$1000 through Curriculum SFT & DPO
 *\*from models without long COT*
-[technical report](https://arxiv.org/abs/2503.10460)
 [GitHub page](https://github.com/Qihoo360/Light-R1)
@@ -128,4 +131,4 @@ Training data are collected from various public sources.
       archivePrefix={},
       url={https://github.com/Qihoo360/Light-R1},
 }
-```

 ---
 base_model:
 - Qwen/Qwen2.5-32B-Instruct
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
 ---
 # Light-R1: Surpassing R1-Distill from Scratch\* with \$1000 through Curriculum SFT & DPO
 *\*from models without long COT*
+[technical report](https://huggingface.co/papers/2503.10460)
 [GitHub page](https://github.com/Qihoo360/Light-R1)
       archivePrefix={},
       url={https://github.com/Qihoo360/Light-R1},
 }
+```