CAE-FastWAM in LeRobot format (converted from amd/CAE-FastWAM; LIBERO 96.7%)

LICENSE

@@ -0,0 +1,202 @@
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NOTICE

@@ -0,0 +1,12 @@
+FastWAM LIBERO checkpoints
+Copyright (c) 2026 Advanced Micro Devices, Inc.
+
+These checkpoints contain a modified version of Wan2.2-TI2V-5B
+(https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B, Wan Team, Alibaba), licensed
+under the Apache License, Version 2.0. The Wan2.2-TI2V-5B weights were
+fine-tuned by Advanced Micro Devices, Inc. using the FastWAM training recipe
+(https://github.com/yuantianyuan01/FastWAM, MIT License).
+
+Training data: LIBERO (Liu et al., NeurIPS 2023; CC BY 4.0), in the LeRobot
+format published as yuanty/LIBERO-fastwam (CC BY 4.0). The dataset is used as
+published. No extra training data was used beyond the FastWAM recipe.

README.md

@@ -0,0 +1,66 @@
+---
+library_name: lerobot
+license: apache-2.0
+pipeline_tag: robotics
+base_model: amd/CAE-FastWAM
+datasets:
+- yuanty/LIBERO-fastwam
+tags:
+- cae_fastwam
+- lerobot
+- libero
+- robotics
+- world-action-model
+---
+
+# CAE-FastWAM (LeRobot format)
+
+[CAE-FastWAM](https://huggingface.co/amd/CAE-FastWAM) converted to the [LeRobot](https://github.com/huggingface/lerobot) checkpoint format. CAE-FastWAM is a [FastWAM](https://arxiv.org/abs/2603.16666) world action model with a Compact Action Expert: a small (32-wide) action expert denoises latent action tokens, and a LIBERO-suite-conditioned action decoder turns them into the action chunk, on top of FastWAM's Wan2.2-TI2V-5B video expert.
+
+The weights are the same as [amd/CAE-FastWAM](https://huggingface.co/amd/CAE-FastWAM); this repo only changes the layout (`config.json`, `model.safetensors`, and the LeRobot pre/post-processors with the per-suite normalisation statistics). It also carries the frozen action-VAE encoder, so the policy can be fine-tuned with the original CAE-FastWAM objective.
+
+> **Note:** loading this checkpoint needs the `cae_fastwam` policy type, which is not in a LeRobot release yet. This card will be updated with install instructions once it is available in LeRobot.
+
+## Inputs and outputs
+
+| Feature | Type | Shape |
+| --- | --- | --- |
+| `observation.images.image` (agent view) | visual | (3, 224, 224) |
+| `observation.images.image2` (wrist view) | visual | (3, 224, 224) |
+| `observation.state` | state | (8,) |
+| `action` | action | (7,) |
+
+Select the LIBERO suite with `--policy.task_suite` (`libero_spatial`, `libero_object`, `libero_goal` or `libero_10`); evaluate one suite per run.
+
+## Results
+
+LIBERO, bfloat16, 10 denoising steps, 50 episodes per task:
+
+| Suite | Success rate | Episodes |
+| --- | ---: | ---: |
+| libero_spatial | 97.0% | 500 |
+| libero_object | 99.8% | 500 |
+| libero_goal | 94.4% | 500 |
+| libero_10 | 95.6% | 500 |
+| **Average** | **96.7%** | 2000 |
+
+Reproduce (per suite; `--env.episode_length=700` for `libero_10`), on one AMD Instinct MI355X:
+
+```bash
+lerobot-eval --policy.path=amd/CAE-FastWAM-lerobot --policy.task_suite=libero_spatial \
+  --env.type=libero --env.task=libero_spatial \
+  --env.observation_height=256 --env.observation_width=256 --env.episode_length=400 \
+  --eval.batch_size=5 --eval.n_episodes=50 --seed=42
+```
+
+LIBERO stack: the one pinned by LeRobot's LIBERO benchmark image (hf-libero 0.1.4, robosuite 1.4.0, MuJoCo 3.3.1), CPU physics, OSMesa rendering. The MuJoCo version matters: with MuJoCo 3.8.1 the `libero_spatial` task 5 scene settles differently and the same evaluation scored 94.5% on average. Please report the MuJoCo version with LIBERO results.
+
+For reference, the [amd/CAE-FastWAM](https://huggingface.co/amd/CAE-FastWAM) card reports 97.28 ± 0.20% with GEAK-optimized inference and a GPU-simulated LIBERO (mean of 11 runs of 2000 episodes).
+
+## Fine-tuning
+
+The checkpoint holds the frozen action-VAE encoder and decoder, so `lerobot-train --policy.path=amd/CAE-FastWAM-lerobot --policy.task_suite=<suite> --accelerator.mixed_precision=bf16 ...` fine-tunes the video and action experts with the original CAE-FastWAM objective, one suite per run.
+
+## Provenance and license
+
+Converted from [amd/CAE-FastWAM](https://huggingface.co/amd/CAE-FastWAM) (Apache-2.0, Advanced Micro Devices, Inc.), a fine-tune of [Wan2.2-TI2V-5B](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B) with the [FastWAM](https://github.com/yuantianyuan01/FastWAM) recipe on LIBERO. See `LICENSE` and `NOTICE`.

SHA256SUMS

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+cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30  LICENSE
+ce18712e4a1c6577dd7ec0970b4ebd61835763155149d8c9ec390529d7bf20f2  model.safetensors
+07b1f41737ff5020427958e08e62c07a176ae395e39d7e41e1f237defa38378a  NOTICE
+60c427e478f68f902bb019e50ffe9a0e55f71799faa7a24130cca31150f92161  policy_postprocessor.json
+d7eaf2818654f5f87424b23096096d437719d1a7e5f3dfa3ec5cbfd958c0829a  policy_postprocessor_step_0_cae_fastwam_suite_unnormalizer.safetensors
+8cdc442a212b6d414644dfdd130fdd291483282a9cad8b3db56dcda2ec5a8d57  policy_preprocessor.json
+21d67e2e1a64200163b7ae04c08aecde9f451e7ed4f386d35be3116dc3d8cdba  policy_preprocessor_step_4_cae_fastwam_suite_normalizer.safetensors
+9e28a2b08d21e0ecd28d160841120da0a41b953607e59465e02f2558156628c3  README.md

config.json

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+{
+    "type": "cae_fastwam",
+    "n_obs_steps": 1,
+    "input_features": {
+        "observation.images.image": {
+            "type": "VISUAL",
+            "shape": [
+                3,
+                224,
+                224
+            ]
+        },
+        "observation.images.image2": {
+            "type": "VISUAL",
+            "shape": [
+                3,
+                224,
+                224
+            ]
+        },
+        "observation.state": {
+            "type": "STATE",
+            "shape": [
+                8
+            ]
+        }
+    },
+    "output_features": {
+        "action": {
+            "type": "ACTION",
+            "shape": [
+                7
+            ]
+        }
+    },
+    "device": "cpu",
+    "dtype": "bfloat16",
+    "use_amp": false,
+    "use_peft": false,
+    "push_to_hub": true,
+    "repo_id": null,
+    "private": null,
+    "tags": [
+        "libero",
+        "world-action-model"
+    ],
+    "license": "apache-2.0",
+    "pretrained_path": null,
+    "pretrained_revision": null,
+    "action_dim": 7,
+    "proprio_dim": 8,
+    "action_horizon": 32,
+    "n_action_steps": 10,
+    "num_video_frames": 33,
+    "action_video_freq_ratio": 4,
+    "image_size": [
+        224,
+        448
+    ],
+    "context_len": 128,
+    "use_relative_actions": false,
+    "relative_exclude_joints": [
+        "gripper"
+    ],
+    "action_feature_names": null,
+    "model_id": "Wan-AI/Wan2.2-TI2V-5B",
+    "tokenizer_model_id": "google/umt5-xxl",
+    "text_encoder_model_id": "Wan-AI/Wan2.2-TI2V-5B-Diffusers",
+    "base_model_id": null,
+    "tokenizer_max_len": 128,
+    "load_text_encoder": true,
+    "text_encoder_device": null,
+    "mot_checkpoint_mixed_attn": false,
+    "action_expert_layers": null,
+    "lite_kv_fusion": false,
+    "retracted_1d_rope": false,
+    "world_model_only_conditioning": false,
+    "torch_dtype": null,
+    "prompt_template": "A video recorded from a robot's point of view executing the following instruction: {task}",
+    "num_inference_steps": 10,
+    "inference_seed": 42,
+    "rand_device": "cpu",
+    "text_cfg_scale": 1.0,
+    "negative_prompt": "",
+    "sigma_shift": null,
+    "tiled": false,
+    "fp32_attention": false,
+    "fp32_upcast": false,
+    "compile_action_infer": false,
+    "use_gradient_checkpointing": false,
+    "freeze_video_expert": false,
+    "toggle_action_dimensions": [
+        -1
+    ],
+    "video_scheduler": {
+        "train_shift": 5.0,
+        "infer_shift": 5.0,
+        "num_train_timesteps": 1000
+    },
+    "action_scheduler": {
+        "train_shift": 5.0,
+        "infer_shift": 5.0,
+        "num_train_timesteps": 1000
+    },
+    "loss": {
+        "lambda_video": 1.0,
+        "lambda_action": 1.0
+    },
+    "video_dit_config": {
+        "patch_size": [
+            1,
+            2,
+            2
+        ],
+        "in_dim": 48,
+        "hidden_dim": 3072,
+        "ffn_dim": 14336,
+        "freq_dim": 256,
+        "text_dim": 4096,
+        "out_dim": 48,
+        "num_heads": 24,
+        "attn_head_dim": 128,
+        "num_layers": 30,
+        "eps": 1e-06,
+        "seperated_timestep": true,
+        "use_gradient_checkpointing": false,
+        "video_attention_mask_mode": "first_frame_causal",
+        "action_conditioned": false,
+        "action_dim": 7,
+        "action_group_causal_mask_mode": "group_diagonal",
+        "fp32_attention": false,
+        "fp32_upcast": false
+    },
+    "action_dit_config": {
+        "action_dim": 16,
+        "hidden_dim": 32,
+        "ffn_dim": 256,
+        "num_heads": 24,
+        "attn_head_dim": 128,
+        "num_layers": 30,
+        "text_dim": 4096,
+        "freq_dim": 256,
+        "eps": 1e-06,
+        "use_gradient_checkpointing": false,
+        "fp32_attention": false,
+        "fp32_upcast": false,
+        "use_text_cross_attention": true
+    },
+    "normalization_mapping": {
+        "VISUAL": "IDENTITY",
+        "STATE": "MIN_MAX",
+        "ACTION": "MIN_MAX"
+    },
+    "optimizer_lr": 0.0001,
+    "optimizer_weight_decay": 0.01,
+    "action_latent_tokens": 8,
+    "action_latent_dim": 16,
+    "action_decoder_hidden_dim": 128,
+    "action_encoder_hidden_dim": 128,
+    "action_encoder_variational": true,
+    "delta_action_dims": [
+        0,
+        1,
+        2,
+        3,
+        4,
+        5
+    ],
+    "task_suites": [
+        "libero_spatial",
+        "libero_object",
+        "libero_goal",
+        "libero_10"
+    ],
+    "task_suite": null
+}

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+  "name": "policy_postprocessor",
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+      "config": {
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+          -1
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policy_preprocessor.json

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+  "name": "policy_preprocessor",
+  "steps": [
+    {
+      "registry_name": "rename_observations_processor",
+      "config": {
+        "rename_map": {}
+      }
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+      "config": {}
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+      "config": {
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+          "action"
+        ],
+        "task_suites": [
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+          "libero_10"
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+  ]
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