Views
No views yet
meta-llama/Llama-3.2-1B-Instruct, from the paper
Are Latent Reasoning Models Easily Interpretable? (Dilgren & Wiegreffe, 2026).pytorch_model.bin — the state dict as
saved by the training framework. It is not a from_pretrained-style model; it is loaded by
the paper's evaluation code, which builds the base model and applies this checkpoint.model_paths.yaml. Download it to the expected location with:hf download connordilgren/llama32-1b-prontoqa-codi pytorch_model.bin --local-dir checkpoints/codi_trained_models/prontoqa_llama1b_latent_baseline/Llama-3.2-1B-Instruct/ep_10/lr_0.0008/seed_11checkpoints/codi_trained_models/prontoqa_llama1b_latent_baseline/Llama-3.2-1B-Instruct/ep_10/lr_0.0008/seed_11/pytorch_model.bin, which is the path referenced for this model
(llama → prontoqa → codi) in model_paths.yaml. See the
repository README for full setup and evaluation instructions.1@misc{dilgren2026latentreasoningmodelseasily,
2 title={Are Latent Reasoning Models Easily Interpretable?},
3 author={Connor Dilgren and Sarah Wiegreffe},
4 year={2026},
5 eprint={2604.04902},
6 archivePrefix={arXiv},
7 primaryClass={cs.LG},
8 url={https://arxiv.org/abs/2604.04902},
9}