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