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

.gitattributes

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README.md

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+---
+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
+
+**LOTUS** (direct LM-head supervision, no CODI) checkpoint fine-tuned from `meta-llama/Llama-3.2-3B-Instruct` on GSM8k-Aug, from the paper
+[Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers](https://arxiv.org/abs/2606.31779).
+This is the LOTUS model.
+
+- **GSM8K (GSM8k-Aug) test accuracy:** 70.05% (924/1319)
+- **Latent config:** K = 6 blocks, c_thought = 25 tokens/block, 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). This loads the safetensors straight from this
+repo and runs the latent loop — no separate checkpoint file needed:
+```bash
+python scripts/eval.py \
+  --model_id yingfanbot/gsm-lotus-llama3b \
+  --datasets gsm8k --n_looped_iters 6 --c_thought 25 --bf16
+```
+Yields 70.05% on GSM8k-Aug (verified by loading this repo's safetensors directly).
+
+## 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}
+}
+```

config.json

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+{
+  "_name_or_path": "meta-llama/Llama-3.2-3B-Instruct",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 3072,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 24,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.2",
+  "use_cache": true,
+  "vocab_size": 128259
+}

generation_config.json

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+{
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+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.46.2"
+}

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