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Model: DatarusAI/Datarus-R1-14B-preview Source: Original Platform
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---
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license: apache-2.0
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library_name: transformers
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language:
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- en
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base_model:
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- Qwen/Qwen2.5-14B
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pipeline_tag: text-generation
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---
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# Datarus-R1-14B-preview
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<div align="center">
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<img src="https://i.postimg.cc/7hsStNgm/logo-icon-2-1.png" alt="Datarus Logo" width="150"/>
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[](https://huggingface.co/DatarusAI/Datarus-R1-14B-preview)
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[](LICENSE)
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[](https://datarus.ai)
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[](https://chat.datarus.ai)
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[](https://arxiv.org/abs/2508.13382)
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</div>
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## 🚀 Overview
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**Datarus-R1-14B-Preview** is a 14B-parameter open-weights language model fine-tuned from Qwen2.5-14B-Instruct, designed to act as a virtual data analyst and graduate-level problem solver. Unlike traditional models trained on isolated Q&A pairs, Datarus learns from complete analytical trajectories—including reasoning steps, code execution, error traces, self-corrections, and final conclusions—all captured in a ReAct-style notebook format.
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### Key Highlights
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- **🎯 State-of-the-art efficiency**: Surpasses similar-sized models and competes with 32B+ models while using 18-49% fewer tokens
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- **🔄 Dual reasoning interfaces**: Supports both Agentic (ReAct) mode for interactive analysis and Reflection (CoT) mode for concise documentation
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- **📊 Superior performance**: Achieves up to 30% higher accuracy on AIME 2024/2025 and LiveCodeBench
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- **💡 "AHA-moment" pattern**: Exhibits efficient hypothesis refinement in 1-2 iterations, avoiding circular reasoning loops
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## 🔗 Quick Links
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- 🌐 **Website**: [https://datarus.ai](https://datarus.ai)
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- 💬 **Try the Demo**: [https://chat.datarus.ai](https://chat.datarus.ai)
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- 🛠️ **Jupyter Agent**: [GitHub Repository](https://github.com/DatarusAI/Datarus-JupyterAgent)
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- 📄 **Paper**: [Datarus-R1: An Adaptive Multi-Step Reasoning LLM](https://arxiv.org/abs/2508.13382)
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## 📊 Performance
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### Benchmark Results
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| Benchmark | Datarus-R1-14B-Preview | QwQ-32B | Phi-4-reasoning | DeepSeek-R1-Distill-14B |
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|-----------|----------------|---------|-----------------|-------------------------|
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| **LiveCodeBench v6** | 57.7 | 56.6 | 52.6 | 48.6 |
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| **AIME 2024** | 70.1 | 76.2 | 74.6* | - |
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| **AIME 2025** | 66.2 | 66.2 | 63.1* | - |
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| **GPQA Diamond** | 62.1 | 60.1 | 55.0 | 58.6 |
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*Reported values from official papers
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### Token Efficiency and Performance
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<div align="center">
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<img src="https://i.postimg.cc/NMSppNM4/perf-efficiency.png" alt="LCB-Efficiency" width="600"/>
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<img src="https://i.postimg.cc/nV341Ssf/efficiency.png" alt="Efficiency" width="600" />
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</div>
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## 🎯 Model Card
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### Model Details
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- **Model Type**: Language Model for Reasoning and Data Analysis
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- **Parameters**: 14.8B
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- **Training Data**: 144,000 synthetic analytical trajectories across finance, medicine, numerical analysis, and other quantitative domains + A curated collection of reasoning datasets.
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- **Language**: English
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- **License**: Apache 2.0
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### Intended Use
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#### Primary Use Cases
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- **Data Analysis**: Automated data exploration, statistical analysis, and visualization
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- **Mathematical Problem Solving**: Graduate-level mathematics including AIME-level problems
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- **Code Generation**: Creating analytical scripts and solving programming challenges
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- **Scientific Reasoning**: Complex problem-solving in physics, chemistry, and other sciences
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- **Interactive Notebooks**: Building complete analysis notebooks with iterative refinement
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### Dual Mode Usage
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#### Agentic Mode (for interactive analysis)
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- Use `<step>`, `<thought>`, `<action>`, `<action_input>`, `<observation>` tags
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- Enables iterative code execution and refinement
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- Best for data analysis, simulations, and exploratory tasks
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#### Reflection Mode (for documentation)
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- Use `<think>` and `<answer>` tags
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- Produces compact, self-contained reasoning chains
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- Best for mathematical proofs, explanations, and reports
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## 📚 Citation
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```bibtex
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@article{benchaliah2025datarus,
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title={Datarus-R1: An Adaptive Multi-Step Reasoning LLM for Automated Data Analysis},
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author={Ben Chaliah, Ayoub and Dellagi, Hela},
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journal={arXiv preprint arXiv:2508.13382},
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year={2025}
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}
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```
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## 🤝 Contributing
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We welcome contributions! Please see our [GitHub repository](https://github.com/DatarusAI/Datarus-JupyterAgent) for:
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- Bug reports and feature requests
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- Pull requests
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- Discussion forums
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## 📄 License
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This model is released under the Apache 2.0 License.
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## 🙏 Acknowledgments
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We thank the Qwen team for the excellent base model and the open-source community for their valuable contributions.
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## 📧 Contact
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- **Email**: ayoub1benchaliah@gmail.com, hela.dellagi@outlook.com
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- **Website**: [https://datarus.ai](https://datarus.ai)
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- **Demo**: [https://chat.datarus.ai](https://chat.datarus.ai)
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---
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<div align="center">
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<strong>Experience the future of AI-powered data analysis with Datarus-R1</strong>
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[Try Demo](https://chat.datarus.ai) | [View Code](https://github.com/DatarusAI/Datarus-JupyterAgent) | [Read Paper](https://arxiv.org/abs/2508.13382)
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</div>
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## ⭐ Support
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If you find this model and Agent pipeline useful, please consider __Like/Star__! Your support helps us continue improving the project.
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Found a bug or have a feature request? Please open an issue on GitHub.
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---
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<p align="center">Made with ❤️ by the Datarus Team from Paris</p>
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||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<step>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</step>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<thought>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</thought>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151669": {
|
||||
"content": "<action_input>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151670": {
|
||||
"content": "</action_input>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151671": {
|
||||
"content": "<observation>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151672": {
|
||||
"content": "</observation>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151673": {
|
||||
"content": "<stop_analysis>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151674": {
|
||||
"content": "</stop_analysis>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151675": {
|
||||
"content": "<answer>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151676": {
|
||||
"content": "</answer>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"bos_token": "<｜begin▁of▁sentence｜>",
|
||||
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<｜end▁of▁sentence｜>",
|
||||
"extra_special_tokens": {},
|
||||
"legacy": true,
|
||||
"model_max_length": 16384,
|
||||
"pad_token": "<｜end▁of▁sentence｜>",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizerFast",
|
||||
"unk_token": null,
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:32a129e966ee9764180961812d9147361a751ea8185eee6fa4c7acdc0fe4a7f4
|
||||
size 8760
|
||||
Reference in New Issue
Block a user