Streaming SFT support (#3101)

* working

* fixes

* deprecate --iterable; cleanup

* pretrain_multipack_buffer_size -> streaming_multipack_buffer_size

* improvements

* tests

* remove unused

* docs, examples

* nit

* nit

* add val_set_size validation

* val

* nit

* min

* coderabbito

* cleanup

* nit

* add depr warning, cleanup

* nit

* fix test, fix quarto

* fix

* review comments

* review comments

* fix

tests/e2e/integrations/test_kd.py

@@ -25,7 +25,7 @@ def min_cfg(temp_dir):
         "liger_rms_norm": True,
         "liger_glu_activation": True,
         "torch_compile": True,
-        "chat_template": "llama3",
+        "chat_template": "qwen3",
         "kd_trainer": True,
         "kd_ce_alpha": 0.1,
         "kd_alpha": 0.9,

tests/e2e/test_streaming.py

@@ -0,0 +1,73 @@
+"""E2E tests for streaming dataset functionality"""
+
+# pylint: disable=duplicate-code
+
+import pytest
+
+from axolotl.common.datasets import load_datasets
+from axolotl.train import train
+from axolotl.utils.config import normalize_config, validate_config
+from axolotl.utils.dict import DictDefault
+
+from .utils import check_model_output_exists, check_tensorboard
+
+
+class TestStreamingDatasets:
+    """Test case for streaming datasets"""
+
+    @pytest.mark.parametrize(
+        "sample_packing",
+        [True, False],
+    )
+    def test_streaming_dataset(self, temp_dir, sample_packing):
+        """Test streaming datasets"""
+
+        cfg = DictDefault(
+            {
+                "base_model": "HuggingFaceTB/SmolLM2-135M",
+                "flash_attention": True,
+                "sequence_len": 1024,
+                "sample_packing": sample_packing,
+                "pretrain_multipack_attn": sample_packing,
+                "streaming_multipack_buffer_size": 10000,
+                "dataset_processes": 1,
+                "special_tokens": {
+                    "pad_token": "<|endoftext|>",
+                },
+                "datasets": [
+                    {
+                        "path": "mhenrichsen/alpaca_2k_test",
+                        "type": "alpaca",
+                    },
+                ],
+                # Streaming config
+                "streaming": True,
+                "max_steps": 3,
+                "micro_batch_size": 1,
+                "gradient_accumulation_steps": 1,
+                "val_set_size": 0.0,
+                "output_dir": temp_dir,
+                "learning_rate": 0.00001,
+                "optimizer": "adamw_torch_fused",
+                "lr_scheduler": "cosine",
+                "save_safetensors": True,
+                "bf16": "auto",
+                "use_tensorboard": True,
+                "save_first_step": False,
+            }
+        )
+
+        cfg = validate_config(cfg)
+        normalize_config(cfg)
+        dataset_meta = load_datasets(cfg=cfg)
+
+        train(cfg=cfg, dataset_meta=dataset_meta)
+        check_model_output_exists(temp_dir, cfg)
+
+        # Verify training actually happened by checking loss decrease
+        check_tensorboard(
+            temp_dir + "/runs",
+            "train/train_loss",
+            3.0,
+            "Train Loss (%s) is too high",
+        )