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 Settings

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

885be8e

verified ·

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@@ -7,55 +7,91 @@ tags:
 - full
 - generated_from_trainer
 model-index:
-- name: hero_run_2_fix_conversations
   results: []
 ---
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-# hero_run_2_fix_conversations
-This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the mlfoundations-dev/hero_run_2_fix_conversations dataset.
-## Model description
-More information needed
-## Intended uses & limitations
-More information needed
-## Training and evaluation data
-More information needed
 ## Training procedure
 ### Training hyperparameters
 The following hyperparameters were used during training:
 - learning_rate: 8e-05
-- train_batch_size: 1
-- eval_batch_size: 8
 - seed: 42
 - distributed_type: multi-GPU
 - num_devices: 256
 - gradient_accumulation_steps: 2
 - total_train_batch_size: 512
-- total_eval_batch_size: 2048
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 5.0
-### Training results
 ### Framework versions
 - Transformers 4.46.1
 - Pytorch 2.3.0
 - Datasets 3.1.0
 - Tokenizers 0.20.3

 - full
 - generated_from_trainer
 model-index:
+- name: OpenThinker2-7B
   results: []
+datasets:
+- open-thoughts/OpenThoughts2-1M
 ---
+<p align="center">
+    <img src="https://huggingface.co/datasets/open-thoughts/open-thoughts-114k/resolve/main/open_thoughts.png" width="50%">
+</p>
+# OpenThinker2-7B
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the
+[OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset.
+The [OpenThinker2-7B](https://huggingface.co/open-thoughts/OpenThinker2-7B) model delivers performance comparable to state-of-the-art 7B models like DeepSeek-R1-Distill-7B, outperforming it on GPQA-D and LCBv2, and having comparable scores on AIME25, AMC23, and MATH500.
+This model improves upon our previous [OpenThinker-7B](https://huggingface.co/open-thoughts/OpenThinker-7B) model, which was trained on 114k examples from [OpenThoughts-114k](https://huggingface.co/datasets/open-thoughts/open-thoughts-114k).
+The numbers reported in the table below are evaluated with our open-source tool [Evalchemy](https://github.com/mlfoundations/Evalchemy).
+| Model            | Open Data? | Avg  | AIME24 | AIME25 | AMC23 | MATH500 | GPQA-D | LCBv2 |
+| ---------------- | ----- | ---- | ------ | ------ | ----- | ------- | ------ | ----- |
+| OpenThinker-7B   | ✅     | 48.9 | 31.3   | 23.3   | 74.5  | 83.2    | 42.9   | 38.0  |
+| OpenThinker2-7B  | ✅     | 61.0 | 50.0   | 33.3   | 89.5  | 88.4    | 49.3   | 55.6  |
+| 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
+This model was trained on the [OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset.
+The [OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset was constructed by augmenting [OpenThoughts-114k](https://huggingface.co/datasets/open-thoughts/open-thoughts-114k) with existing datasets like [OpenR1](https://huggingface.co/open-r1), as well as additional math and code reasoning data.
+We generate the additional math and code data by ablating on various question generation methodologies and sampling from the highest performing ones.
+See the [OpenThoughts2-1M](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M) dataset page or our [blog post]() for additional information.
+## Intended uses & limitations
+Apache 2.0 License
 ## Training procedure
+We used 32 8xA100 nodes to train the model for 36 hours.
 ### Training hyperparameters
 The following hyperparameters were used during training:
 - learning_rate: 8e-05
 - seed: 42
 - distributed_type: multi-GPU
 - num_devices: 256
 - gradient_accumulation_steps: 2
 - total_train_batch_size: 512
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 5.0
 ### Framework versions
 - Transformers 4.46.1
 - Pytorch 2.3.0
 - Datasets 3.1.0
 - Tokenizers 0.20.3
+More info can be found in our repository: [https://github.com/open-thoughts/open-thoughts](https://github.com/open-thoughts/open-thoughts).
+# Citation
+```
+@misc{openthoughts,
+  author = {Team, OpenThoughts},
+  month = apr,
+  title = {{Open Thoughts}},
+  howpublished = {https://open-thoughts.ai},
+  year = {2025}
+}
+```
+# Links
+- 📊 [OpenThoughts2 and OpenThinker2 Blog Post]()
+- 💻 [Open Thoughts GitHub Repository](https://github.com/open-thoughts/open-thoughts)
+- 🧠 [OpenThoughts2-1M dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M)
+- 🤖 [OpenThinker2-7B model](https://huggingface.co/open-thoughts/OpenThinker2-7B) - this model.
+- 🤖 [OpenThinker2-32B model](https://huggingface.co/open-thoughts/OpenThinker2-32B)