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README.md

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+---
+license: other
+library_name: transformers
+tags:
+- reasoning
+- context-learning
+- synthetic-data
+- transformers
+---
+
+# Interplay-LM Context Pretrain Models
+
+This repository is organized by context-mixture setting. Each top-level directory corresponds to one pretraining setting used in the context experiments.
+
+Within each setting:
+
+- `base/` stores the final pretraining checkpoint used to initialize RL.
+- `rl/` stores the final RL checkpoints for each experiment variant.
+
+Only inference-relevant Hugging Face files are included.
+
+## Included settings
+
+- `idzoo_0.9zoo_0.1teacher`
+- `idzoo_0.99zoo_0.01teacher`
+- `idzoo_0.999zoo_0.001teacher`
+
+## Load
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+repo_id = "Interplay-LM-Reasoning/context_pretrain"
+subdir = "idzoo_0.99zoo_0.01teacher/rl/contextzoo_0.99zoo_0.01teacher_process_strict"
+
+tokenizer = AutoTokenizer.from_pretrained(repo_id, subfolder=subdir)
+model = AutoModelForCausalLM.from_pretrained(repo_id, subfolder=subdir)
+```
+
+## 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},
+}
+```