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--- |
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license: apache-2.0 |
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datasets: |
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- hamishivi/gsm8k-symbolic |
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language: |
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- en |
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base_model: |
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- hamishivi/tess2-v0.3-base |
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--- |
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# TESS 2 v0.3 Symbolic - A Math-specific Tuned Diffusion LM |
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This model is the TESS 2 model trained on GSM8k symbolic data found [here](https://huggingface.co/datasets/hamishivi/gsm8k-symbolic), adapted from [here](https://github.com/HKUNLP/diffusion-of-thoughts). This model is a simplex-based diffusion model adapted from Mistral v0.1 7B, further trained on Dolma 1.7 and Tulu 2 SFT data. |
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For more details, please check out our paper [TESS-2: A Large-Scale, Generalist Diffusion Language Model](https://arxiv.org/abs/2502.13917). |
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This is the model based on Mistral v0.3 and trained on GSM8k data. |
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This model will only work with our custom codebase found [here](https://github.com/hamishivi/tess-2) -- please go there to see details on how to run training and inference. |
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## Using this model |
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To run this model, first clone https://github.com/hamishivi/tess-2. |
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Then, after creating a python environment with the correct packages, you can run inference via a ui with: |
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```sh |
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./shell_scripts/run_interactive_demo.sh hamishivi/tess2-v0.3 |
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``` |
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This allows you to directly interact with the model, and shows the diffusion generation process. |
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For training or other evaluations, please see our main repository. |
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## Citation |
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If you find this work useful, please cite this work as follows. |
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```bibtex |
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@misc{taeivison2025tess2, |
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title={{TESS 2: A Large-Scale Generalist Diffusion Language Model}}, |
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author={Jaesung Tae and Hamish Ivison and Sachin Kumar and Arman Cohan}, |
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year={2025}, |
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eprint={2502.13917}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2502.13917}, |
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} |
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``` |