fix(hub): pin pretrained artifacts to one commit

src/lerobot/configs/eval.py

@@ -48,8 +48,13 @@ class EvalPipelineConfig:
         if policy_path:
             yaml_overrides = parser.get_yaml_overrides("policy")
             cli_overrides = parser.get_cli_overrides("policy") or []
+            pretrained_revision = parser.parse_arg("pretrained_revision", cli_overrides)
+            if pretrained_revision is None:
+                pretrained_revision = parser.parse_arg("pretrained_revision", yaml_overrides)
             self.policy = PreTrainedConfig.from_pretrained(
-                policy_path, cli_overrides=yaml_overrides + cli_overrides
+                policy_path,
+                revision=pretrained_revision,
+                cli_overrides=yaml_overrides + cli_overrides,
             )
             self.policy.pretrained_path = Path(policy_path)
 

src/lerobot/configs/policies.py

@@ -29,7 +29,7 @@ from huggingface_hub.errors import HfHubHTTPError
 from lerobot.optim import LRSchedulerConfig, OptimizerConfig
 from lerobot.utils.constants import ACTION, OBS_STATE
 from lerobot.utils.device_utils import auto_select_torch_device, is_amp_available, is_torch_device_available
-from lerobot.utils.hub import HubMixin
+from lerobot.utils.hub import HubMixin, extract_commit_hash
 
 from .types import FeatureType, PolicyFeature
 
@@ -82,6 +82,26 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):  # type: igno
     # Optional Hub revision (commit hash, branch, or tag) to pin the pretrained model version.
     pretrained_revision: str | None = None
 
+    @property
+    def _commit_hash(self) -> str | None:
+        """Resolved Hub commit for this runtime load; never serialized."""
+        return self.__dict__.get("_runtime_commit_hash")
+
+    @property
+    def _commit_hash_source(self) -> str | None:
+        """Hub repo whose revision resolved to ``_commit_hash``."""
+        return self.__dict__.get("_runtime_commit_hash_source")
+
+    def _set_hub_commit_hash(self, commit_hash: str | None, source: str | None) -> None:
+        self.__dict__["_runtime_commit_hash"] = commit_hash
+        self.__dict__["_runtime_commit_hash_source"] = source if commit_hash is not None else None
+
+    def get_hub_revision(self, source: str | Path | None, revision: str | None = None) -> str | None:
+        """Return the pinned revision when ``source`` owns the resolved commit."""
+        if self._commit_hash is not None and self._commit_hash_source == str(source):
+            return self._commit_hash
+        return revision
+
     def __post_init__(self) -> None:
         if not self.device or not is_torch_device_available(self.device):
             auto_device = auto_select_torch_device()
@@ -182,7 +202,8 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):  # type: igno
     ) -> T:
         model_id = str(pretrained_name_or_path)
         config_file: str | None = None
-        if Path(model_id).is_dir():
+        is_local = Path(model_id).is_dir()
+        if is_local:
             if CONFIG_NAME in os.listdir(model_id):
                 config_file = os.path.join(model_id, CONFIG_NAME)
             else:
@@ -208,8 +229,12 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):  # type: igno
         if config_file is None:
             raise FileNotFoundError(f"{CONFIG_NAME} not found in {model_id}")
 
+        commit_hash = None if is_local else extract_commit_hash(config_file, revision)
         with open(config_file) as f:
             config = json.load(f)
+        # Runtime Hub metadata must never become part of the serialized config schema.
+        config.pop("_commit_hash", None)
+        config.pop("_commit_hash_source", None)
 
         # Resolve the concrete config subclass from the serialized "type" tag, then parse
         # the config (with CLI overrides) directly for that class. The "type" key is
@@ -231,4 +256,6 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):  # type: igno
 
         cli_overrides = policy_kwargs.pop("cli_overrides", [])
         with draccus.config_type("json"):
-            return draccus.parse(config_cls, config_file, args=cli_overrides)
+            parsed_config = draccus.parse(config_cls, config_file, args=cli_overrides)
+        parsed_config._set_hub_commit_hash(commit_hash, model_id)
+        return parsed_config

src/lerobot/configs/train.py

@@ -172,8 +172,16 @@ class TrainPipelineConfig(HubMixin):
             )
             self.reward_model.pretrained_path = str(Path(reward_model_path))
         elif policy_path:
-            overrides = parser.get_yaml_overrides("policy") + (parser.get_cli_overrides("policy") or [])
-            self.policy = PreTrainedConfig.from_pretrained(policy_path, cli_overrides=overrides)
+            yaml_overrides = parser.get_yaml_overrides("policy")
+            cli_overrides = parser.get_cli_overrides("policy") or []
+            pretrained_revision = parser.parse_arg("pretrained_revision", cli_overrides)
+            if pretrained_revision is None:
+                pretrained_revision = parser.parse_arg("pretrained_revision", yaml_overrides)
+            self.policy = PreTrainedConfig.from_pretrained(
+                policy_path,
+                revision=pretrained_revision,
+                cli_overrides=yaml_overrides + cli_overrides,
+            )
             self.policy.pretrained_path = Path(policy_path)
         elif self.resume:
             self._resolve_resume_checkpoint()

src/lerobot/policies/factory.py

@@ -171,6 +171,9 @@ def make_pre_post_processors(
         ValueError: If no processor factory exists for the given policy configuration type.
     """
     if pretrained_path:
+        revision_resolver = getattr(policy_cfg, "get_hub_revision", None)
+        if callable(revision_resolver):
+            pretrained_revision = revision_resolver(pretrained_path, pretrained_revision)
         if isinstance(policy_cfg, GrootConfig):
             from .groot.processor_groot import make_groot_pre_post_processors_from_pretrained
 

src/lerobot/policies/groot/modeling_groot.py

@@ -37,6 +37,7 @@ from torch import Tensor
 
 from lerobot.configs import FeatureType, PolicyFeature
 from lerobot.utils.constants import ACTION, OBS_IMAGES
+from lerobot.utils.hub import extract_commit_hash
 from lerobot.utils.import_utils import _transformers_available, require_package
 
 from ..pretrained import PreTrainedPolicy
@@ -195,6 +196,8 @@ class GrootPolicy(PreTrainedPolicy):
         )
 
         model_id = str(pretrained_name_or_path)
+        if config is not None:
+            revision = config.get_hub_revision(model_id, revision)
         is_finetuned_checkpoint = False
 
         # Check if this is a fine-tuned LeRobot checkpoint (has model.safetensors)
@@ -204,7 +207,7 @@ class GrootPolicy(PreTrainedPolicy):
             else:
                 # Try to download the safetensors file to check if it exists
                 try:
-                    hf_hub_download(
+                    resolved_model_file = hf_hub_download(
                         repo_id=model_id,
                         filename=SAFETENSORS_SINGLE_FILE,
                         revision=revision,
@@ -214,6 +217,10 @@ class GrootPolicy(PreTrainedPolicy):
                         token=token,
                         local_files_only=local_files_only,
                     )
+                    resolved_commit_hash = extract_commit_hash(resolved_model_file, revision)
+                    revision = resolved_commit_hash or revision
+                    if config is not None and config._commit_hash is None:
+                        config._set_hub_commit_hash(resolved_commit_hash, model_id)
                     is_finetuned_checkpoint = True
                 except HfHubHTTPError:
                     is_finetuned_checkpoint = False

src/lerobot/policies/pi0/modeling_pi0.py

@@ -53,6 +53,7 @@ from lerobot.utils.constants import (
     OBS_LANGUAGE_TOKENS,
     OBS_STATE,
 )
+from lerobot.utils.hub import extract_commit_hash
 
 from ..common.flow_matching import euler_integrate, sample_noise, sample_time_beta
 from ..common.vla_utils import (
@@ -814,6 +815,8 @@ class PI0Policy(PreTrainedPolicy):
                 **kwargs,
             )
 
+        revision = config.get_hub_revision(pretrained_name_or_path, revision)
+
         # Initialize model without loading weights
         # Check if dataset_stats were provided in kwargs
         model = cls(config, **kwargs)
@@ -832,9 +835,13 @@ class PI0Policy(PreTrainedPolicy):
                     resume_download=kwargs.get("resume_download"),
                     proxies=kwargs.get("proxies"),
                     token=kwargs.get("token"),
-                    revision=kwargs.get("revision"),
+                    revision=revision,
                     local_files_only=kwargs.get("local_files_only", False),
                 )
+                if config._commit_hash is None:
+                    config._set_hub_commit_hash(
+                        extract_commit_hash(resolved_file, revision), str(pretrained_name_or_path)
+                    )
                 from safetensors.torch import load_file
 
                 original_state_dict = load_file(resolved_file)

src/lerobot/policies/pi05/modeling_pi05.py

@@ -50,6 +50,7 @@ from lerobot.utils.constants import (
     OBS_LANGUAGE_ATTENTION_MASK,
     OBS_LANGUAGE_TOKENS,
 )
+from lerobot.utils.hub import extract_commit_hash
 
 from ..common.flow_matching import euler_integrate, sample_noise, sample_time_beta
 from ..common.vla_utils import (
@@ -779,6 +780,8 @@ class PI05Policy(PreTrainedPolicy):
                 **kwargs,
             )
 
+        revision = config.get_hub_revision(pretrained_name_or_path, revision)
+
         # Initialize model without loading weights
         # Check if dataset_stats were provided in kwargs
         model = cls(config, **kwargs)
@@ -797,9 +800,13 @@ class PI05Policy(PreTrainedPolicy):
                     resume_download=kwargs.get("resume_download"),
                     proxies=kwargs.get("proxies"),
                     token=kwargs.get("token"),
-                    revision=kwargs.get("revision"),
+                    revision=revision,
                     local_files_only=kwargs.get("local_files_only", False),
                 )
+                if config._commit_hash is None:
+                    config._set_hub_commit_hash(
+                        extract_commit_hash(resolved_file, revision), str(pretrained_name_or_path)
+                    )
                 from safetensors.torch import load_file
 
                 original_state_dict = load_file(resolved_file)

src/lerobot/policies/pi0_fast/modeling_pi0_fast.py

@@ -55,6 +55,7 @@ from lerobot.utils.constants import (
     OBS_LANGUAGE_ATTENTION_MASK,
     OBS_LANGUAGE_TOKENS,
 )
+from lerobot.utils.hub import extract_commit_hash
 
 from ..common.vla_utils import pad_vector, prepare_attention_masks_4d, resize_with_pad_torch
 from ..pretrained import PreTrainedPolicy, T
@@ -808,6 +809,8 @@ class PI0FastPolicy(PreTrainedPolicy):
                 **kwargs,
             )
 
+        revision = config.get_hub_revision(pretrained_name_or_path, revision)
+
         # Initialize model without loading weights
         # Check if dataset_stats were provided in kwargs
         model = cls(config, **kwargs)
@@ -826,9 +829,13 @@ class PI0FastPolicy(PreTrainedPolicy):
                     resume_download=kwargs.get("resume_download"),
                     proxies=kwargs.get("proxies"),
                     token=kwargs.get("token"),
-                    revision=kwargs.get("revision"),
+                    revision=revision,
                     local_files_only=kwargs.get("local_files_only", False),
                 )
+                if config._commit_hash is None:
+                    config._set_hub_commit_hash(
+                        extract_commit_hash(resolved_file, revision), str(pretrained_name_or_path)
+                    )
                 from safetensors.torch import load_file
 
                 original_state_dict = load_file(resolved_file)

src/lerobot/policies/pretrained.py

@@ -33,7 +33,7 @@ from lerobot.__version__ import __version__
 from lerobot.configs import PreTrainedConfig
 from lerobot.configs.train import TrainPipelineConfig
 from lerobot.utils.device_utils import resolve_safetensors_device
-from lerobot.utils.hub import HubMixin
+from lerobot.utils.hub import HubMixin, extract_commit_hash
 
 from .utils import log_model_loading_keys
 
@@ -190,6 +190,7 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
                 **kwargs,
             )
         model_id = str(pretrained_name_or_path)
+        revision = config.get_hub_revision(model_id, revision)
         instance = cls(config, **kwargs)
         if os.path.isdir(model_id):
             print("Loading weights from local directory")
@@ -208,6 +209,8 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
                     token=token,
                     local_files_only=local_files_only,
                 )
+                if config._commit_hash is None:
+                    config._set_hub_commit_hash(extract_commit_hash(model_file, revision), model_id)
                 policy = cls._load_as_safetensor(instance, model_file, config.device, strict)
             except HfHubHTTPError as e:
                 raise FileNotFoundError(

src/lerobot/policies/xvla/modeling_xvla.py

@@ -31,6 +31,7 @@ from torch import Tensor, nn
 
 from lerobot.configs import PreTrainedConfig
 from lerobot.utils.constants import ACTION, OBS_LANGUAGE_TOKENS, OBS_STATE
+from lerobot.utils.hub import extract_commit_hash
 from lerobot.utils.import_utils import _transformers_available, require_package
 
 from ..common.vla_utils import pad_vector, resize_with_pad
@@ -459,6 +460,7 @@ class XVLAPolicy(PreTrainedPolicy):
             )
 
         model_id = str(pretrained_name_or_path)
+        revision = config.get_hub_revision(model_id, revision)
         instance = cls(config, **kwargs)
         # step 2: locate model.safetensors
         if os.path.isdir(model_id):
@@ -480,6 +482,8 @@ class XVLAPolicy(PreTrainedPolicy):
                     token=token,
                     local_files_only=local_files_only,
                 )
+                if config._commit_hash is None:
+                    config._set_hub_commit_hash(extract_commit_hash(model_file, revision), model_id)
             except HfHubHTTPError as e:
                 raise FileNotFoundError(f"model.safetensors not found on the Hub at {model_id}") from e
 

src/lerobot/processor/delta_action_processor.py

@@ -132,10 +132,20 @@ class MapDeltaActionToRobotActionStep(RobotActionProcessorStep):
     def transform_features(
         self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
     ) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
-        for axis in ["x", "y", "z", "gripper"]:
+        for axis in ["x", "y", "z"]:
             features[PipelineFeatureType.ACTION].pop(f"delta_{axis}", None)
+        features[PipelineFeatureType.ACTION].pop("gripper", None)
 
-        for feat in ["enabled", "target_x", "target_y", "target_z", "target_wx", "target_wy", "target_wz"]:
+        for feat in [
+            "enabled",
+            "target_x",
+            "target_y",
+            "target_z",
+            "target_wx",
+            "target_wy",
+            "target_wz",
+            "gripper_vel",
+        ]:
             features[PipelineFeatureType.ACTION][f"{feat}"] = PolicyFeature(
                 type=FeatureType.ACTION, shape=(1,)
             )

src/lerobot/processor/pipeline.py

@@ -47,7 +47,7 @@ from safetensors.torch import load_file, save_file
 from lerobot.configs import PipelineFeatureType, PolicyFeature
 from lerobot.types import EnvAction, EnvTransition, PolicyAction, RobotAction, RobotObservation, TransitionKey
 from lerobot.utils.constants import HF_LEROBOT_HOME
-from lerobot.utils.hub import HubMixin
+from lerobot.utils.hub import HubMixin, extract_commit_hash
 
 from .converters import batch_to_transition, create_transition, transition_to_batch
 
@@ -727,6 +727,10 @@ class DataProcessorPipeline[TInput, TOutput](HubMixin):
 
         # 1. Load configuration using simplified 3-way logic
         loaded_config, base_path = cls._load_config(model_id, config_filename, hub_download_kwargs)
+        if not is_local_source:
+            commit_hash = extract_commit_hash(base_path, revision)
+            if commit_hash is not None:
+                hub_download_kwargs["revision"] = commit_hash
 
         # 2. Validate configuration and handle migration
         cls._validate_loaded_config(model_id, loaded_config, config_filename)

src/lerobot/rollout/context.py

@@ -161,7 +161,12 @@ class RolloutContext:
 
 def _load_pretrained_policy(policy_config: PreTrainedConfig) -> PreTrainedPolicy:
     """Load policy weights, keeping adapter and base-model revisions independent."""
-    pretrained_revision = policy_config.pretrained_revision
+    revision_resolver = getattr(policy_config, "get_hub_revision", None)
+    pretrained_revision = (
+        revision_resolver(policy_config.pretrained_path, policy_config.pretrained_revision)
+        if callable(revision_resolver)
+        else policy_config.pretrained_revision
+    )
     policy_class = get_policy_class(policy_config.type)
 
     if not policy_config.use_peft:

src/lerobot/utils/hub.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import builtins
+import re
 from pathlib import Path
 from tempfile import TemporaryDirectory
 from typing import Any, TypeVar
@@ -23,6 +24,29 @@ from huggingface_hub.utils import validate_hf_hub_args
 from .constants import CHECKPOINTS_DIR
 
 T = TypeVar("T", bound="HubMixin")
+REGEX_COMMIT_HASH = re.compile(r"^[0-9a-f]{40}$")
+
+
+def extract_commit_hash(resolved_file: str | Path | None, revision: str | None = None) -> str | None:
+    """Extract the immutable commit hash backing a resolved Hub file.
+
+    Hub cache paths contain ``snapshots/<commit_hash>/``. If the requested
+    revision is already a full commit hash, use it as a fallback for custom
+    cache layouts that do not expose the standard snapshot path.
+    """
+    if resolved_file is not None:
+        path_parts = Path(resolved_file).parts
+        try:
+            snapshot_index = path_parts.index("snapshots")
+            commit_hash = path_parts[snapshot_index + 1]
+            if REGEX_COMMIT_HASH.fullmatch(commit_hash):
+                return commit_hash
+        except (ValueError, IndexError):
+            pass
+
+    if revision is not None and REGEX_COMMIT_HASH.fullmatch(revision):
+        return revision
+    return None
 
 
 def find_latest_hub_checkpoint(

tests/configs/test_policy_revision_pinning.py

@@ -0,0 +1,77 @@
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+from dataclasses import dataclass
+
+from lerobot.configs import PreTrainedConfig
+
+
+@PreTrainedConfig.register_subclass("revision_pinning_test")
+@dataclass
+class RevisionPinningTestConfig(PreTrainedConfig):
+    @property
+    def observation_delta_indices(self) -> list | None:
+        return None
+
+    @property
+    def action_delta_indices(self) -> list | None:
+        return None
+
+    @property
+    def reward_delta_indices(self) -> list | None:
+        return None
+
+    def get_optimizer_preset(self):
+        raise NotImplementedError
+
+    def get_scheduler_preset(self):
+        raise NotImplementedError
+
+    def validate_features(self) -> None:
+        pass
+
+
+def test_pretrained_config_pins_resolved_hub_commit(monkeypatch, tmp_path):
+    commit_hash = "a" * 40
+    snapshot_dir = tmp_path / "models--user--policy" / "snapshots" / commit_hash
+    RevisionPinningTestConfig(device="cpu").save_pretrained(snapshot_dir)
+    calls = []
+
+    def fake_hub_download(**kwargs):
+        calls.append(kwargs)
+        return str(snapshot_dir / "config.json")
+
+    monkeypatch.setattr("lerobot.configs.policies.hf_hub_download", fake_hub_download)
+
+    config = PreTrainedConfig.from_pretrained("user/policy", revision="main")
+
+    assert calls[0]["revision"] == "main"
+    assert config._commit_hash == commit_hash
+    assert config._commit_hash_source == "user/policy"
+    assert config.get_hub_revision("user/policy", "main") == commit_hash
+    assert config.get_hub_revision("user/base-policy", "base-tag") == "base-tag"
+
+
+def test_runtime_commit_hash_is_not_serialized(tmp_path):
+    config = RevisionPinningTestConfig(device="cpu")
+    config._set_hub_commit_hash("a" * 40, "user/policy")
+
+    config.save_pretrained(tmp_path)
+
+    serialized_config = json.loads((tmp_path / "config.json").read_text())
+    assert "_commit_hash" not in serialized_config
+    assert "_commit_hash_source" not in serialized_config
+    assert "_runtime_commit_hash" not in serialized_config
+    assert "_runtime_commit_hash_source" not in serialized_config

tests/policies/test_pretrained_revision_pinning.py

@@ -0,0 +1,122 @@
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+
+from lerobot.policies import factory
+from lerobot.policies.act.configuration_act import ACTConfig
+from lerobot.policies.pretrained import PreTrainedPolicy
+from lerobot.processor import PolicyProcessorPipeline
+
+
+class _MinimalPolicy(PreTrainedPolicy):
+    config_class = ACTConfig
+    name = "minimal_revision_test"
+
+    def get_optim_params(self) -> dict:
+        return {}
+
+    def reset(self) -> None:
+        pass
+
+    def forward(self, batch: dict[str, torch.Tensor]) -> tuple[torch.Tensor, dict | None]:
+        return torch.tensor(0), None
+
+    def predict_action_chunk(self, batch: dict[str, torch.Tensor], **kwargs) -> torch.Tensor:
+        return torch.tensor(0)
+
+    def select_action(self, batch: dict[str, torch.Tensor], **kwargs) -> torch.Tensor:
+        return torch.tensor(0)
+
+
+def _skip_safetensor_loading(monkeypatch):
+    monkeypatch.setattr(
+        _MinimalPolicy,
+        "_load_as_safetensor",
+        classmethod(lambda cls, model, model_file, map_location, strict: model),
+    )
+
+
+def test_policy_weights_use_config_commit_hash(monkeypatch):
+    config = ACTConfig(device="cpu")
+    config._set_hub_commit_hash("a" * 40, "user/policy")
+    calls = []
+
+    def fake_hub_download(**kwargs):
+        calls.append(kwargs)
+        return "/unused/model.safetensors"
+
+    monkeypatch.setattr("lerobot.policies.pretrained.hf_hub_download", fake_hub_download)
+    _skip_safetensor_loading(monkeypatch)
+
+    _MinimalPolicy.from_pretrained("user/policy", config=config, revision="main")
+
+    assert calls[0]["revision"] == "a" * 40
+
+
+def test_policy_does_not_reuse_commit_hash_for_another_repo(monkeypatch):
+    config = ACTConfig(device="cpu")
+    config._set_hub_commit_hash("a" * 40, "user/adapter")
+    calls = []
+
+    def fake_hub_download(**kwargs):
+        calls.append(kwargs)
+        return "/unused/model.safetensors"
+
+    monkeypatch.setattr("lerobot.policies.pretrained.hf_hub_download", fake_hub_download)
+    _skip_safetensor_loading(monkeypatch)
+
+    _MinimalPolicy.from_pretrained("user/base-policy", config=config, revision="base-tag")
+
+    assert calls[0]["revision"] == "base-tag"
+
+
+def test_policy_records_weight_commit_for_explicit_config(monkeypatch):
+    commit_hash = "a" * 40
+    config = ACTConfig(device="cpu")
+
+    def fake_hub_download(**kwargs):
+        return f"/cache/models--user--policy/snapshots/{commit_hash}/model.safetensors"
+
+    monkeypatch.setattr("lerobot.policies.pretrained.hf_hub_download", fake_hub_download)
+    _skip_safetensor_loading(monkeypatch)
+
+    _MinimalPolicy.from_pretrained("user/policy", config=config, revision="main")
+
+    assert config._commit_hash == commit_hash
+    assert config._commit_hash_source == "user/policy"
+
+
+def test_processor_factory_uses_config_commit_hash(monkeypatch):
+    config = ACTConfig(device="cpu")
+    config._set_hub_commit_hash("a" * 40, "user/policy")
+    calls = []
+
+    def fake_from_pretrained(cls, **kwargs):
+        calls.append(kwargs)
+        return PolicyProcessorPipeline(steps=[])
+
+    monkeypatch.setattr(
+        factory.PolicyProcessorPipeline,
+        "from_pretrained",
+        classmethod(fake_from_pretrained),
+    )
+
+    factory.make_pre_post_processors(
+        config,
+        pretrained_path="user/policy",
+        pretrained_revision="main",
+    )
+
+    assert [call["revision"] for call in calls] == ["a" * 40, "a" * 40]

tests/processor/test_pipeline_from_pretrained_helpers.py

@@ -241,6 +241,68 @@ def test_from_pretrained_hub_source_missing_local_state_still_calls_hub(monkeypa
         ProcessorStepRegistry.unregister("hub_state_step")
 
 
+def test_from_pretrained_pins_hub_state_to_config_commit(monkeypatch, tmp_path):
+    """A mutable processor revision is resolved once and reused for state files."""
+
+    @ProcessorStepRegistry.register("pinned_hub_state_step")
+    class PinnedHubStateStep(ProcessorStep):
+        def __init__(self):
+            self.value = torch.tensor(0)
+
+        def __call__(self, transition: EnvTransition) -> EnvTransition:
+            return transition
+
+        def transform_features(
+            self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
+        ) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
+            return features
+
+        def load_state_dict(self, state: dict[str, torch.Tensor]) -> None:
+            self.value = state["value"]
+
+    try:
+        commit_hash = "a" * 40
+        snapshot_dir = tmp_path / "models--user--policy" / "snapshots" / commit_hash
+        snapshot_dir.mkdir(parents=True)
+        config_path = snapshot_dir / "processor.json"
+        config_path.write_text(
+            json.dumps(
+                {
+                    "name": "PinnedHubStatePipeline",
+                    "steps": [
+                        {
+                            "registry_name": "pinned_hub_state_step",
+                            "state_file": "hub_state.safetensors",
+                        }
+                    ],
+                }
+            )
+        )
+        state_path = tmp_path / "downloaded.safetensors"
+        save_file({"value": torch.tensor(7)}, state_path)
+        calls = []
+
+        def fake_hub_download(**kwargs):
+            calls.append(kwargs)
+            if kwargs["filename"] == "processor.json":
+                return str(config_path)
+            return str(state_path)
+
+        monkeypatch.setattr("lerobot.processor.pipeline.hf_hub_download", fake_hub_download)
+
+        pipeline = DataProcessorPipeline.from_pretrained(
+            "user/policy",
+            config_filename="processor.json",
+            revision="main",
+        )
+
+        assert calls[0]["revision"] == "main"
+        assert calls[1]["revision"] == commit_hash
+        assert pipeline.steps[0].value.item() == 7
+    finally:
+        ProcessorStepRegistry.unregister("pinned_hub_state_step")
+
+
 # Config Validation Tests
 
 

tests/utils/test_hub.py

@@ -14,7 +14,7 @@
 
 from unittest.mock import MagicMock
 
-from lerobot.utils.hub import find_latest_hub_checkpoint
+from lerobot.utils.hub import extract_commit_hash, find_latest_hub_checkpoint
 
 
 def _patch_list_files(monkeypatch, files):
@@ -52,3 +52,20 @@ def test_find_latest_hub_checkpoint_ignores_non_step_entries(monkeypatch):
 def test_find_latest_hub_checkpoint_none_when_no_checkpoints(monkeypatch):
     _patch_list_files(monkeypatch, ["config.json", "model.safetensors"])
     assert find_latest_hub_checkpoint("u/run") is None
+
+
+def test_extract_commit_hash_from_hub_snapshot_path():
+    commit_hash = "a" * 40
+    resolved_file = f"/cache/models--user--policy/snapshots/{commit_hash}/config.json"
+
+    assert extract_commit_hash(resolved_file, revision="main") == commit_hash
+
+
+def test_extract_commit_hash_falls_back_to_full_sha_revision():
+    commit_hash = "b" * 40
+
+    assert extract_commit_hash("/custom/cache/config.json", revision=commit_hash) == commit_hash
+
+
+def test_extract_commit_hash_rejects_mutable_revision_without_snapshot():
+    assert extract_commit_hash("/custom/cache/config.json", revision="main") is None