Instructions to use QuantFactory/OpenThinker-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/OpenThinker-7B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("QuantFactory/OpenThinker-7B-GGUF", dtype="auto")

llama-cpp-python

How to use QuantFactory/OpenThinker-7B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/OpenThinker-7B-GGUF",
	filename="OpenThinker-7B.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use QuantFactory/OpenThinker-7B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/OpenThinker-7B-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/OpenThinker-7B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use QuantFactory/OpenThinker-7B-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for QuantFactory/OpenThinker-7B-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for QuantFactory/OpenThinker-7B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/OpenThinker-7B-GGUF to start chatting

Pi new

How to use QuantFactory/OpenThinker-7B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "QuantFactory/OpenThinker-7B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use QuantFactory/OpenThinker-7B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use QuantFactory/OpenThinker-7B-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/OpenThinker-7B-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/OpenThinker-7B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/OpenThinker-7B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.OpenThinker-7B-GGUF-Q4_K_M

List all available models

lemonade list

aashish1904 commited on Jun 17, 2025

Commit

f7bdc28

verified ·

1 Parent(s): 4f99f61

Upload README.md with huggingface_hub

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Files changed (1) hide show

README.md +18 -12

README.md CHANGED Viewed

@@ -29,6 +29,9 @@ This is quantized version of [open-thoughts/OpenThinker-7B](https://huggingface.
     <img src="https://huggingface.co/datasets/open-thoughts/open-thoughts-114k/resolve/main/open_thoughts.png" width="50%">
 </p>
 # OpenThinker-7B
 This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the
@@ -94,20 +97,10 @@ The following hyperparameters were used during training:
 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 = jan,
-  title = {{Open Thoughts}},
-  howpublished = {https://open-thoughts.ai},
-  year = {2025}
-}
-```
 # Links
 - 📊 [Open Thoughts Launch Blog Post](https://www.open-thoughts.ai/blog/launch)
-- 💻  [Open Thoughts GitHub Repository](https://github.com/open-thoughts/open-thoughts)
 - 🧠 [OpenThoughts-114k dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k)
 - 🤖 [OpenThinker-7B model](https://huggingface.co/open-thoughts/OpenThinker-7B) - this model.
 - 📊 [Bespoke-Stratos Blog Post](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation)
@@ -115,3 +108,16 @@ More info can be found in our repository: [https://github.com/open-thoughts/open
 - 🤖 [Bespoke-Stratos-32B model](https://huggingface.co/bespokelabs/Bespoke-Stratos-32B)
 - 🤖 [Bespoke-Stratos-7B model](https://huggingface.co/bespokelabs/Bespoke-Stratos-7B)

     <img src="https://huggingface.co/datasets/open-thoughts/open-thoughts-114k/resolve/main/open_thoughts.png" width="50%">
 </p>
+> [!NOTE]
+> We have released a paper for OpenThoughts! See our paper [here](https://arxiv.org/abs/2506.04178).
 # OpenThinker-7B
 This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the
 More info can be found in our repository: [https://github.com/open-thoughts/open-thoughts](https://github.com/open-thoughts/open-thoughts).
 # Links
+- 📝 [OpenThoughts Paper](https://arxiv.org/abs/2506.04178)
 - 📊 [Open Thoughts Launch Blog Post](https://www.open-thoughts.ai/blog/launch)
+- 💻 [Open Thoughts GitHub Repository](https://github.com/open-thoughts/open-thoughts)
 - 🧠 [OpenThoughts-114k dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k)
 - 🤖 [OpenThinker-7B model](https://huggingface.co/open-thoughts/OpenThinker-7B) - this model.
 - 📊 [Bespoke-Stratos Blog Post](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation)
 - 🤖 [Bespoke-Stratos-32B model](https://huggingface.co/bespokelabs/Bespoke-Stratos-32B)
 - 🤖 [Bespoke-Stratos-7B model](https://huggingface.co/bespokelabs/Bespoke-Stratos-7B)
+# Citation
+```
+@misc{guha2025openthoughtsdatarecipesreasoning,
+  title={OpenThoughts: Data Recipes for Reasoning Models},
+  author={Etash Guha and Ryan Marten and Sedrick Keh and Negin Raoof and Georgios Smyrnis and Hritik Bansal and Marianna Nezhurina and Jean Mercat and Trung Vu and Zayne Sprague and Ashima Suvarna and Benjamin Feuer and Liangyu Chen and Zaid Khan and Eric Frankel and Sachin Grover and Caroline Choi and Niklas Muennighoff and Shiye Su and Wanjia Zhao and John Yang and Shreyas Pimpalgaonkar and Kartik Sharma and Charlie Cheng-Jie Ji and Yichuan Deng and Sarah Pratt and Vivek Ramanujan and Jon Saad-Falcon and Jeffrey Li and Achal Dave and Alon Albalak and Kushal Arora and Blake Wulfe and Chinmay Hegde and Greg Durrett and Sewoong Oh and Mohit Bansal and Saadia Gabriel and Aditya Grover and Kai-Wei Chang and Vaishaal Shankar and Aaron Gokaslan and Mike A. Merrill and Tatsunori Hashimoto and Yejin Choi and Jenia Jitsev and Reinhard Heckel and Maheswaran Sathiamoorthy and Alexandros G. Dimakis and Ludwig Schmidt},
+  year={2025},
+  eprint={2506.04178},
+  archivePrefix={arXiv},
+  primaryClass={cs.LG},
+  url={https://arxiv.org/abs/2506.04178},
+}
+```