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README.md
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- instruct
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base_model: Qwen/Qwen3-4B-Instruct-2507
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datasets:
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language:
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- en
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- code
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## Model Sources
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- **Repository:** [jupyter-agent](https://github.com/huggingface/jupyter-agent)
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- **Dataset:** [jupyter-agent-dataset](https://huggingface.co/datasets/
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- **Blog post:** [Jupyter Agents: training LLMs to reason with notebooks](https://huggingface.co/blog/jupyter-agent-2)
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- **Demo:** [Jupyter Agent 2](https://huggingface.co/spaces/lvwerra/jupyter-agent-2)
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "
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# Load model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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### Training Data
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The model was fine-tuned on the [Jupyter Agent Dataset](https://huggingface.co/datasets/
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- **51,389 synthetic notebooks** (~0.2B tokens, total 1B tokens)
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- **Dataset-grounded QA pairs** from real Kaggle notebooks
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author={Baptiste Colle and Hanna Yukhymenko and Leandro von Werra},
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year={2025},
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publisher={Hugging Face},
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url={https://huggingface.co/
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}
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```
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## Related Work
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- **Dataset:** [jupyter-agent-dataset](https://huggingface.co/datasets/
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- **Thinking version:** [jupyter-agent-qwen3-4b-thinking](https://huggingface.co/
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- **Base model:** [Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)
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- **Benchmark:** [DABStep](https://huggingface.co/spaces/adyen/DABstep)
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- instruct
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base_model: Qwen/Qwen3-4B-Instruct-2507
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datasets:
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- jupyter-agent/jupyter-agent-dataset
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language:
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- en
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- code
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## Model Sources
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- **Repository:** [jupyter-agent](https://github.com/huggingface/jupyter-agent)
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- **Dataset:** [jupyter-agent-dataset](https://huggingface.co/datasets/jupyter-agent/jupyter-agent-dataset)
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- **Blog post:** [Jupyter Agents: training LLMs to reason with notebooks](https://huggingface.co/blog/jupyter-agent-2)
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- **Demo:** [Jupyter Agent 2](https://huggingface.co/spaces/lvwerra/jupyter-agent-2)
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "jupyter-agent/jupyter-agent-qwen3-4b-instruct"
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# Load model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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### Training Data
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The model was fine-tuned on the [Jupyter Agent Dataset](https://huggingface.co/datasets/jupyter-agent/jupyter-agent-dataset), which contains:
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- **51,389 synthetic notebooks** (~0.2B tokens, total 1B tokens)
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- **Dataset-grounded QA pairs** from real Kaggle notebooks
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author={Baptiste Colle and Hanna Yukhymenko and Leandro von Werra},
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year={2025},
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publisher={Hugging Face},
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url={https://huggingface.co/jupyter-agent/jupyter-agent-qwen3-4b-instruct}
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}
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```
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## Related Work
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- **Dataset:** [jupyter-agent-dataset](https://huggingface.co/datasets/jupyter-agent/jupyter-agent-dataset)
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- **Thinking version:** [jupyter-agent-qwen3-4b-thinking](https://huggingface.co/jupyter-agent/jupyter-agent-qwen3-4b-thinking)
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- **Base model:** [Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)
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- **Benchmark:** [DABStep](https://huggingface.co/spaces/adyen/DABstep)
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