Remove manual dataset config - let HF auto-detect

dataset_info.json

@@ -1,19 +0,0 @@
-{
-  "description": "Metis OLMoE Latent Telemetry: SNN routing research dataset with raw telemetry logs",
-  "builder_name": "metis_ol_moe_latent_telemetry",
-  "config_name": "default",
-  "version": "1.0.0",
-  "splits": {
-    "test": {
-      "name": "test",
-      "num_bytes": 818486,
-      "num_examples": 20000,
-      "dataset_name": "metis-ol_mo_e-latent-telemetry"
-    }
-  },
-  "supervised_keys": null,
-  "builder_config": {
-    "name": "default",
-    "version": "1.0.0"
-  }
-}

metis_ol_moe_latent_telemetry.py

@@ -1,69 +0,0 @@
-import os
-import re
-import datasets
-from datasets import Dataset, Features, Value
-
-logger = datasets.logging.get_logger(__name__)
-
-
-class MetisOlMOELatentTelemetry(datasets.GeneratorBasedBuilder):
-    """Metis OLMoE Latent Telemetry dataset for SNN routing research."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description="Raw bare-metal telemetry logs from Metis SNN-quantized OLMoE model",
-            features=Features(
-                {
-                    "tick": Value("int64"),
-                    "best_walker": Value("int64"),
-                    "elapsed_us": Value("int64"),
-                    "source_file": Value("string"),
-                }
-            ),
-            homepage="https://huggingface.co/datasets/rmems/Metis-OLMoE-Latent-Telemetry",
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = os.path.abspath(os.path.join(os.path.dirname(__file__)))
-        
-        # Find all .txt telemetry files
-        txt_files = []
-        for root, dirs, files in os.walk(data_dir):
-            for file in files:
-                if file.endswith(".txt") and ("telemetry" in file or "map_olmoe" in file):
-                    txt_files.append(os.path.join(root, file))
-        
-        logger.info(f"Found {len(txt_files)} telemetry files: {txt_files}")
-        
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepaths": txt_files},
-            ),
-        ]
-
-    def _generate_examples(self, filepaths):
-        """Yields examples from the telemetry text files."""
-        pattern = re.compile(r"tick=(\d+)\s+best_walker=(\d+)\s+elapsed_us=(\d+)")
-        
-        idx = 0
-        for filepath in filepaths:
-            filename = os.path.basename(filepath)
-            with open(filepath, encoding="utf-8") as f:
-                for line in f:
-                    line = line.strip()
-                    if not line:
-                        continue
-                    match = pattern.match(line)
-                    if match:
-                        tick, best_walker, elapsed_us = match.groups()
-                        yield idx, {
-                            "tick": int(tick),
-                            "best_walker": int(best_walker),
-                            "elapsed_us": int(elapsed_us),
-                            "source_file": filename,
-                        }
-                        idx += 1