Initial release

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LICENSE

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NOTICE

@@ -0,0 +1,23 @@
+xLLM Part II model artifacts
+Towards Looped Models Done Right, Part II: Rethinking at Fixed Points
+
+The model weights are distributed under the Apache License, Version 2.0.
+A copy is provided in LICENSE. The xLLM code has its own license in the
+repository root; third-party code retains its original notices.
+
+Tokenizer attribution
+
+The tokenizer is the one the models were trained with: a BPE tokenizer with a
+64,000-token vocabulary that the authors' team trained on a Jais-style data
+mix, which the paper calls Jais64k after Jais (Sengupta et al., 2023), with
+added chat and tool special tokens. It is distributed with the weights under
+the Apache License, Version 2.0, in tokenizer/: tokenizer.json,
+tokenizer_config.json and special_tokens_map.json are copied unchanged. A
+distilled student has no tokenizer/ and uses its teacher's.
+
+Artifact preparation:
+- The trained FP32 tensors are rounded to BF16 and stored in Safetensors
+  shards, keyed as the xLLM model's state dict.
+- config.json holds the release model config; for models with a tokenizer, its
+  tokenizer section points to tokenizer/, and for distilled students its student
+  section names the teacher artifact and its manifest SHA-256.

README.md

@@ -0,0 +1,78 @@
+---
+license: apache-2.0
+library_name: xllm
+pipeline_tag: text-generation
+tags:
+- xllm
+- looped-language-model
+- paper-part2
+- dense
+---
+
+# d4-s
+
+Table 4, S, D4 of *Towards Looped Models Done Right. Part II: Rethinking at Fixed Points*.
+
+> [!IMPORTANT]
+> **Loading this checkpoint requires the xLLM code.** The weights are stored in xLLM's native
+> format (BF16 Safetensors with an xLLM `config.json` and `artifact_manifest.json`). This is not a
+> Hugging Face `transformers` checkpoint: `AutoModel.from_pretrained` cannot load it.
+> Get the code at [https://github.com/ifm-ai/xllm-loop](https://github.com/ifm-ai/xllm-loop) and load the directory with `xllm.paper_part2.artifacts.load_artifact`.
+
+## Model details
+
+| | |
+| --- | --- |
+| Model | dense Transformer of 4 blocks, untied output layer; width 1,536, 24 heads (6 KV heads), SwiGLU FFN 4,352 |
+| Parameters | 301,217,280, including the embedding and output layers |
+| Evaluation | full KV cache |
+| Training | recipe `s_d4`: 5,120 updates of 512 x 8,192 tokens (21.47B), AdamW, warmup-stable-decay |
+| Weights | BF16 Safetensors: the training checkpoint's FP32 weights rounded to BF16 |
+| Tokenizer | `tokenizer/`, the Jais64k tokenizer of training |
+
+## Download
+
+```bash
+hf download IFM/LoopedLM-P2-d4-s --local-dir d4-s
+```
+
+The xLLM loader checks the directory against `artifact_manifest.json`: it rejects symbolic links
+and files the manifest does not list, apart from the `.gitattributes` file and the
+`.cache/huggingface/` folder that `hf download --local-dir` adds. Download into a directory as
+above, not into the Hub cache (`~/.cache/huggingface/hub`), whose files are symbolic links.
+
+## Use
+
+Evaluate with `eval_paper_part2.py` from the xLLM repository:
+
+```bash
+ENABLE_FLASH_ATTENTION_3=true python eval_paper_part2.py --artifact d4-s \
+    --data /path/to/eval-data/data.json --out out ppl
+```
+
+`data.json` and the evaluation inputs come from `release/paper-part2/prepare-eval-data.py
+--output /path/to/eval-data`.
+
+`xllm.paper_part2.artifacts.load_artifact("d4-s")` verifies the directory and returns the model
+config fields and the BF16 state dict on CPU.
+
+`artifact_manifest.json` records the size and SHA-256 of every file in this repository.
+
+## Paper and citation
+
+*Towards Looped Models Done Right. Part II: Rethinking at Fixed Points*: https://github.com/ifm-ai/xllm-loop/blob/main/papers/part2.pdf
+
+```bibtex
+@misc{huang2026fixedpoints,
+  title  = {Towards Looped Models Done Right. Part II: Rethinking at Fixed Points},
+  author = {Benhao Huang and Chufan Shi and Junlin Chen and Shicheng Wen and Zhengzhong Liu and Eric Xing and Xuezhe Ma},
+  year   = {2026},
+  url    = {https://github.com/ifm-ai/xllm-loop/blob/main/papers/part2.pdf}
+}
+```
+
+## License
+
+The weights are released under the Apache License 2.0 (`LICENSE`); `NOTICE` records the
+tokenizer's attribution and how the artifact was prepared. The xLLM code is distributed under its
+own license.

artifact_manifest.json

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+  "files": [
+    {
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+      "size_bytes": 11357
+    },
+    {
+      "path": "NOTICE",
+      "sha256": "c7a79ff1f727571ac24b0b79cd6a1f3179142d66b7c83cedda5cb18b4097c241",
+      "size_bytes": 1205
+    },
+    {
+      "path": "README.md",
+      "sha256": "4e02c1663d95ce9c27f18be3ebd6257e69a053b5d3ee19bc06f2b2cb3a65d7a7",
+      "size_bytes": 2937
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+      "size_bytes": 2802
+    },
+    {
+      "path": "tokenizer/special_tokens_map.json",
+      "sha256": "431aa39c50202573663aad96e19dd5195091bd03c8e9b95f0dbecbb9c67b95da",
+      "size_bytes": 70
+    },
+    {
+      "path": "tokenizer/tokenizer.json",
+      "sha256": "7f25e969fb47990f9ad6728ff8d595e988d6756cf034a10a51913260b05fa4af",
+      "size_bytes": 4948085
+    },
+    {
+      "path": "tokenizer/tokenizer_config.json",
+      "sha256": "c4c81a35fe7a549d6d16f1464a19a81e548c086beb66f9f39bd994259d0b5ec0",
+      "size_bytes": 48991
+    }
+  ],
+  "format": "xllm-native-bf16-safetensors",
+  "manifest_sha256": "f5eb54b954e98399f927d9eea09707fcf22512fa39dab1035e74df1ab8c07720",
+  "model": {
+    "dtype": "bfloat16",
+    "index": "model.safetensors.index.json",
+    "shards": 1,
+    "tensor_count": 39
+  },
+  "release": "paper-part2",
+  "schema_version": 1,
+  "source": {
+    "checkpoint_id": "d4-s",
+    "table_row": "Table 4, S, D4"
+  }
+}

config.json

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+{
+  "model": {
+    "apply_attn_gate": false,
+    "apply_bias_term": true,
+    "apply_rmsnorm": true,
+    "arch": "transformer",
+    "attention_dropout": 0.0,
+    "attn_act_func": "softmax",
+    "attn_gate_func": "silu",
+    "awm_orthogonal_update": false,
+    "causal_attn_backend": "flash",
+    "causal_conv_backend": "triton",
+    "causal_conv_weight_normalization": true,
+    "causal_conv_width": 4,
+    "chunk_size": 1024,
+    "ddp_backend": "fsdp1",
+    "dense_prelude_diagonal_a_init": 1.0,
+    "dense_prelude_diagonal_dt_init": 1.0,
+    "dense_prelude_input_injection": "none",
+    "dense_prelude_input_layers": "",
+    "dense_prelude_source_layer": -1,
+    "dropout": 0.0,
+    "expert_inter_dim": 0,
+    "ffn_hidden_dim": 4352,
+    "fused_block": false,
+    "fused_output_layer": true,
+    "head_dim": 64,
+    "hidden_dropout": 0.0,
+    "huginn_antithetic_sampling": false,
+    "huginn_backprop_depth": null,
+    "huginn_coda_layers": 1,
+    "huginn_depth_control": false,
+    "huginn_depth_prior": "none",
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+    "huginn_diagonal_a_init": 1.0,
+    "huginn_diagonal_dt_init": 1.0,
+    "huginn_hierarchical_h_cycles": 2,
+    "huginn_hierarchical_l_cycles": 3,
+    "huginn_hierarchical_state": "none",
+    "huginn_input_injection": "diagonal",
+    "huginn_ortho_projection_eps": 1e-06,
+    "huginn_poisson_lognormal_max": 64,
+    "huginn_poisson_lognormal_sigma": 0.5,
+    "huginn_poisson_lognormal_target_mean": 5.0,
+    "huginn_prelude_layers": 1,
+    "huginn_prelude_norm": "none",
+    "huginn_prelude_orthogonal": false,
+    "huginn_recurrent_exit_norm": "none",
+    "huginn_recurrent_layers": null,
+    "huginn_sampling_scheme": "fixed",
+    "huginn_split_module_repeats": 1,
+    "huginn_state_init": "zero",
+    "init_embed_std": null,
+    "init_logits_std": null,
+    "init_mode": "gaussian",
+    "init_std": 0.02,
+    "layernorm_eps": 1e-05,
+    "layernorm_num_groups": 1,
+    "layerwise_ckpt": false,
+    "loop_diagonal_a_init": 1.0,
+    "loop_diagonal_dt_init": 1.0,
+    "loop_end_layers": null,
+    "loop_input_injection": "none",
+    "loop_start_layer": 0,
+    "loop_times": 1,
+    "memory_efficient_norm": false,
+    "model_dim": 1536,
+    "moe_expert_backend": "sequential",
+    "moe_permutation_backend": "torch",
+    "moe_router_bias": false,
+    "moe_router_bias_update_rate": null,
+    "moe_router_scaling_factor": null,
+    "moe_router_score_func": "sigmoid",
+    "mova_backend": "sequential",
+    "norm_affine": true,
+    "num_activated_experts": 0,
+    "num_activated_values": 0,
+    "num_dense_layers": null,
+    "num_experts": 0,
+    "num_heads": 24,
+    "num_kv_heads": 6,
+    "num_layers": 4,
+    "num_shared_experts": 0,
+    "num_values": 0,
+    "output_size": -1,
+    "qknorm": false,
+    "recompute_attention": false,
+    "recompute_awk": false,
+    "recompute_fc1_out": false,
+    "recompute_fc3_out": false,
+    "recompute_logits": false,
+    "recompute_q": false,
+    "recompute_router": false,
+    "recompute_v": false,
+    "residual_func": "base",
+    "residual_heads": null,
+    "rmsnorm_eps": 1e-06,
+    "rope_base": 1000000.0,
+    "rope_head_dim": 64,
+    "sca_backend": "swift",
+    "scale_emb": false,
+    "swiglu": true,
+    "timenorm_backend": "cub",
+    "timenorm_beta1": 0.999,
+    "timenorm_beta2": 0.9999,
+    "timenorm_eps": 1e-05,
+    "timenorm_num_groups": 32,
+    "v_head_dim": null,
+    "vocab_size": 64256
+  },
+  "tokenizer": {
+    "path": "tokenizer",
+    "type": "huggingface"
+  }
+}

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tokenizer/special_tokens_map.json

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+}

tokenizer/tokenizer_config.json

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