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Model: yingfanbot/gsm-lotus-llama3b-nl
Source: Original Platform

README.md

@@ -0,0 +1,42 @@
+---
+license: mit
+base_model: meta-llama/Llama-3.2-3B-Instruct
+library_name: transformers
+pipeline_tag: text-generation
+tags: [latent-reasoning, looped-transformer, gsm8k, lotus]
+---
+
+# gsm-lotus-llama3b-nl
+
+LOTUS trained on **natural-language chain-of-thought**, fine-tuned from `meta-llama/Llama-3.2-3B-Instruct`,
+from the paper
+[Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers](https://arxiv.org/abs/2606.31779).
+Direct step-aligned supervision through the base LM head (no aux decoder, no CODI); the latent blocks are
+supervised against natural-language reasoning steps rather than formatted math expressions.
+
+- **GSM8K (GSM8k-Aug) test accuracy:** 68.54% (904/1319)
+- **Latent config:** K = 6 blocks, **c_thought = 50** tokens/block (NL steps are ~2.7x longer than math-expr,
+  so c=50 covers ~98.8% of steps), n_looped_iters = 6
+- **Base:** meta-llama/Llama-3.2-3B-Instruct (vocab 128256 -> 128259 for 3 latent tokens)
+
+## Loading
+`from_pretrained` loads the weights only — the looped padded architecture needs the LOTUS code
+([code repo](https://github.com/yingfan-bot/lotus)).
+
+## Reproduce the number above
+Run in the pinned env (torch 2.7 / transformers 4.46.2) — note **`--c_thought 50`** for this NL model:
+```bash
+python scripts/eval.py \
+  --model_id yingfanbot/gsm-lotus-llama3b-nl \
+  --datasets gsm8k --n_looped_iters 6 --c_thought 50 --bf16
+```
+
+## Citation
+```bibtex
+@article{fan2026bridging,
+  title={Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers},
+  author={Fan, Ying and Svete, Anej and Lee, Kangwook},
+  journal={arXiv preprint arXiv:2606.31779},
+  year={2026}
+}
+```