Instructions to use procedure2012/Titan-Math-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procedure2012/Titan-Math-Pro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="procedure2012/Titan-Math-Pro")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("procedure2012/Titan-Math-Pro") model = AutoModel.from_pretrained("procedure2012/Titan-Math-Pro") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: mit
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library_name: transformers
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---
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# Titan-Math-Pro
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<!-- markdownlint-disable first-line-h1 -->
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<!-- markdownlint-disable html -->
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<!-- markdownlint-disable no-duplicate-header -->
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<div align="center">
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<img src="figures/fig1.png" width="60%" alt="Titan-Math-Pro" />
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</div>
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<hr>
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<div align="center" style="line-height: 1;">
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<a href="LICENSE" style="margin: 2px;">
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<img alt="License" src="figures/fig2.png" style="display: inline-block; vertical-align: middle;"/>
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</a>
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</div>
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## 1. Introduction
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Titan-Math-Pro is a mathematics-first model trained on verified proofs and competition problems with process supervision.
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## 2. Evaluation Results
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### Comprehensive Benchmark Results
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<div align="center">
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| | Benchmark | NumeriX | Titan-base | ProofNet | Titan-Math-Pro |
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|---|---|---|---|---|---|
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| **Core Reasoning Tasks** | Math Reasoning | 0.589 | 0.595 | 0.577 | 0.633 |
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| | Logical Reasoning | 0.816 | 0.818 | 0.793 | 0.850 |
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| | Common Sense | 0.749 | 0.735 | 0.776 | 0.783 |
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| **Language Understanding** | Reading Comprehension | 0.707 | 0.731 | 0.743 | 0.760 |
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| | Question Answering | 0.595 | 0.595 | 0.642 | 0.649 |
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| | Text Classification | 0.815 | 0.817 | 0.831 | 0.849 |
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| | Sentiment Analysis | 0.779 | 0.780 | 0.765 | 0.818 |
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| **Generation Tasks** | Code Generation | 0.703 | 0.682 | 0.702 | 0.730 |
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| | Creative Writing | 0.693 | 0.670 | 0.658 | 0.700 |
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| | Dialogue Generation | 0.683 | 0.677 | 0.656 | 0.702 |
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| | Summarization | 0.793 | 0.765 | 0.771 | 0.805 |
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| **Specialized Capabilities** | Translation | 0.802 | 0.815 | 0.814 | 0.826 |
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| | Knowledge Retrieval | 0.667 | 0.672 | 0.687 | 0.718 |
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| | Instruction Following | 0.756 | 0.750 | 0.741 | 0.798 |
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| | Safety Evaluation | 0.762 | 0.739 | 0.734 | 0.779 |
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</div>
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### Overall Performance Summary
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The Titan-Math-Pro demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
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## 3. Chat Website & API Platform
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We offer a chat interface and API for you to interact with Titan-Math-Pro. Please check our official website for more details.
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## 4. How to Run Locally
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Please refer to our code repository for more information about running Titan-Math-Pro locally.
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### Temperature
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We recommend setting the temperature parameter to 0.6.
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## 5. License
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This repository is released under the mit license. The model supports commercial use.
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## 6. Contact
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If you have any questions, please contact us at math@titan-compute.com.
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