Instructions to use Interplay-LM-Reasoning/context_pretrain_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Interplay-LM-Reasoning/context_pretrain_2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Interplay-LM-Reasoning/context_pretrain_2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| license: other | |
| library_name: transformers | |
| tags: | |
| - reasoning | |
| - context-learning | |
| - pretraining | |
| - synthetic-data | |
| - transformers | |
| # 0.99zoo_op2-20+0.01teacher_op2 | |
| 99% zoo op2-20, 1% teacher op2 pretraining mixture. This directory contains the final op2-only pretraining checkpoint and corresponding final RL checkpoints. | |
| This is a context B pretraining checkpoint where the teacher component uses only op2. | |
| ## Citation | |
| ```bibtex | |
| @misc{zhang2025interplaypretrainingmidtrainingrl, | |
| title={On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models}, | |
| author={Charlie Zhang and Graham Neubig and Xiang Yue}, | |
| year={2025}, | |
| eprint={2512.07783}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| url={https://arxiv.org/abs/2512.07783}, | |
| } | |
| ``` | |