Instructions to use open-thoughts/OpenThinker2-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use open-thoughts/OpenThinker2-7B with Transformers:

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

pipe = pipeline("text-generation", model="open-thoughts/OpenThinker2-7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("open-thoughts/OpenThinker2-7B")
model = AutoModelForCausalLM.from_pretrained("open-thoughts/OpenThinker2-7B")
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

vLLM

How to use open-thoughts/OpenThinker2-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "open-thoughts/OpenThinker2-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "open-thoughts/OpenThinker2-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/open-thoughts/OpenThinker2-7B

SGLang

How to use open-thoughts/OpenThinker2-7B 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 "open-thoughts/OpenThinker2-7B" \
    --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": "open-thoughts/OpenThinker2-7B",
		"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 "open-thoughts/OpenThinker2-7B" \
        --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": "open-thoughts/OpenThinker2-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use open-thoughts/OpenThinker2-7B with Docker Model Runner:
```
docker model run hf.co/open-thoughts/OpenThinker2-7B
```

sedrickkeh commited on Apr 3, 2025

Commit

9308ef6

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1 Parent(s): 885be8e

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@@ -33,7 +33,6 @@ The numbers reported in the table below are evaluated with our open-source tool
 | R1-Distill-7B    | ❌     | 61.3 | 57.3   | 33.3   | 92.0  | 89.6    | 47.3   | 48.4  |
 | OlympicCoder-7B  | ✅     | 42.4 | 20.7   | 15.3   | 63.0  | 74.8    | 25.3   | 55.4  |
 | OpenR1-7B        | ✅     | 48.4 | 48.7   | 34.7   | 88.5  | 87.8    | 21.2   | 9.5   |
-| Nemotron-Nano-8B | ⚠️    | 69.0 | 61.3   | 45.3   | 94.0  | 89.0    | 55.9   | 68.4  |
 ## Data

 | R1-Distill-7B    | ❌     | 61.3 | 57.3   | 33.3   | 92.0  | 89.6    | 47.3   | 48.4  |
 | OlympicCoder-7B  | ✅     | 42.4 | 20.7   | 15.3   | 63.0  | 74.8    | 25.3   | 55.4  |
 | OpenR1-7B        | ✅     | 48.4 | 48.7   | 34.7   | 88.5  | 87.8    | 21.2   | 9.5   |
 ## Data