set download to use revision

docs/config.qmd

@@ -90,6 +90,7 @@ datasets:
     shards: # Optional[int] number of shards to split data into
     name: # Optional[str] name of dataset configuration to load
     train_on_split: train # Optional[str] name of dataset split to load from
+    revision: # Optional[str] The specific revision of the dataset to use when loading from the Hugging Face Hub. This can be a commit hash, tag, or branch name. If not specified, the latest version will be used. This parameter is ignored for local datasets.
 
     # Optional[str] fastchat conversation type, only used with type: sharegpt
     conversation: # Options (see Conversation 'name'): https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py

src/axolotl/utils/data/sft.py

@@ -242,6 +242,7 @@ def load_tokenized_prepared_datasets(
                     name=config_dataset.name,
                     streaming=True,
                     token=use_auth_token,
+                    revision=config_dataset.revision,
                 )
                 ds_from_hub = True
             except (FileNotFoundError, ConnectionError, HFValidationError, ValueError):
@@ -346,6 +347,7 @@ def load_tokenized_prepared_datasets(
                     streaming=False,
                     data_files=config_dataset.data_files,
                     token=use_auth_token,
+                    revision=config_dataset.revision,
                     **load_ds_kwargs,
                 )
             elif ds_from_cloud and remote_file_system:
@@ -380,6 +382,7 @@ def load_tokenized_prepared_datasets(
                         repo_id=config_dataset.path,
                         repo_type="dataset",
                         filename=config_dataset.data_files,
+                        revision=config_dataset.revision,
                     )
                 elif isinstance(config_dataset.data_files, list):
                     fp = []
@@ -389,6 +392,7 @@ def load_tokenized_prepared_datasets(
                                 repo_id=config_dataset.path,
                                 repo_type="dataset",
                                 filename=file,
+                                revision=config_dataset.revision,
                             )
                         )
                 else:
@@ -433,8 +437,8 @@ def load_tokenized_prepared_datasets(
                 config_dataset=config_dataset,
                 tokenizer=tokenizer,
                 cfg=cfg,
-                dataset=ds,
                 d_base_type=d_base_type,
+                dataset=ds,
                 d_prompt_style=d_prompt_style,
                 processor=processor,
             )

tests/test_datasets.py

@@ -267,6 +267,74 @@ class TestDatasetPreparation(unittest.TestCase):
             assert "attention_mask" in dataset.features
             assert "labels" in dataset.features
 
+    def test_load_hub_with_revision(self):
+        """Verify that processing data from the hub works with a specific revision"""
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            prepared_path = Path(tmp_dir) / "prepared"
+            cfg = DictDefault(
+                {
+                    "tokenizer_config": "huggyllama/llama-7b",
+                    "sequence_len": 1024,
+                    "datasets": [
+                        {
+                            "path": "mhenrichsen/alpaca_2k_test",
+                            "type": "alpaca",
+                            "revision": "d05c1cb",
+                        },
+                    ],
+                }
+            )
+
+            dataset, _ = load_tokenized_prepared_datasets(
+                self.tokenizer, cfg, prepared_path
+            )
+
+            assert len(dataset) == 2000
+            assert "input_ids" in dataset.features
+            assert "attention_mask" in dataset.features
+            assert "labels" in dataset.features
+
+    def test_load_local_hub_with_revision(self):
+        """Verify that a local copy of a hub dataset can be loaded with a specific revision"""
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            tmp_ds_path = Path("mhenrichsen/alpaca_2k_test")
+            tmp_ds_path.mkdir(parents=True, exist_ok=True)
+            snapshot_download(
+                repo_id="mhenrichsen/alpaca_2k_test",
+                repo_type="dataset",
+                local_dir=tmp_ds_path,
+                revision="d05c1cb",
+            )
+
+            prepared_path = Path(tmp_dir) / "prepared"
+            cfg = DictDefault(
+                {
+                    "tokenizer_config": "huggyllama/llama-7b",
+                    "sequence_len": 1024,
+                    "datasets": [
+                        {
+                            "path": "mhenrichsen/alpaca_2k_test",
+                            "ds_type": "parquet",
+                            "type": "alpaca",
+                            "data_files": [
+                                "mhenrichsen/alpaca_2k_test/alpaca_2000.parquet",
+                            ],
+                            "revision": "d05c1cb",
+                        },
+                    ],
+                }
+            )
+
+            dataset, _ = load_tokenized_prepared_datasets(
+                self.tokenizer, cfg, prepared_path
+            )
+
+            assert len(dataset) == 2000
+            assert "input_ids" in dataset.features
+            assert "attention_mask" in dataset.features
+            assert "labels" in dataset.features
+            shutil.rmtree(tmp_ds_path)
+
 
 if __name__ == "__main__":
     unittest.main()