update

notebooks/.ipynb_checkpoints/convert-lm-eval-harness-checkpoint.ipynb

@@ -33,7 +33,7 @@
     "task_name = 'hellaswag'\n",
     "data = load_dataset(task_name)\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        text = item['ctx'] + item['endings'][int(item['label'])]\n",
     "        f.write(\n",
@@ -62,7 +62,7 @@
     "task_name = 'boolq'\n",
     "data = load_dataset(task_name)\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        text = f\"{item['passage']}\\nQuestion: {item['question']}?\\nAnswer: {item['answer']}\"\n",
     "        f.write(\n",
@@ -119,7 +119,7 @@
     "task_name = 'arc_challenge'\n",
     "data = load_dataset('ai2_arc', 'ARC-Challenge')\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        i_a = item['choices']['label'].index(item['answerKey'])\n",
     "        q = item['question']\n",
@@ -169,7 +169,7 @@
     "task_name = 'arc_easy'\n",
     "data = load_dataset('ai2_arc', 'ARC-Easy')\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        i_a = item['choices']['label'].index(item['answerKey'])\n",
     "        q = item['question']\n",
@@ -182,31 +182,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 17,
    "id": "b3b98d73-4729-40a1-a5ea-51a3bcfd7ffe",
    "metadata": {},
    "outputs": [
     {
      "ename": "FileNotFoundError",
-     "evalue": "Unable to resolve any data file that matches '['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**']' at /var/cr06_data/jue@together.xyz/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']",
+     "evalue": "Couldn't find a dataset script at /var/cr06_data/jue@together.xyz/target-data/notebooks/juewang/target-data/target-data.py or any data file in the same directory. Couldn't find 'juewang/target-data' on the Hugging Face Hub either: FileNotFoundError: Unable to resolve any data file that matches ['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**'] in dataset repository juewang/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']",
      "output_type": "error",
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m../\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "Cell \u001b[0;32mIn[17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mjuewang/target-data\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msplit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtrain\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1785\u001b[0m, in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, storage_options, **config_kwargs)\u001b[0m\n\u001b[1;32m   1780\u001b[0m verification_mode \u001b[38;5;241m=\u001b[39m VerificationMode(\n\u001b[1;32m   1781\u001b[0m     (verification_mode \u001b[38;5;129;01mor\u001b[39;00m VerificationMode\u001b[38;5;241m.\u001b[39mBASIC_CHECKS) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m save_infos \u001b[38;5;28;01melse\u001b[39;00m VerificationMode\u001b[38;5;241m.\u001b[39mALL_CHECKS\n\u001b[1;32m   1782\u001b[0m )\n\u001b[1;32m   1784\u001b[0m \u001b[38;5;66;03m# Create a dataset builder\u001b[39;00m\n\u001b[0;32m-> 1785\u001b[0m builder_instance \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset_builder\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1786\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1787\u001b[0m \u001b[43m    \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1788\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1789\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1790\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1791\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfeatures\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfeatures\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1792\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1793\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1794\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1795\u001b[0m \u001b[43m    \u001b[49m\u001b[43muse_auth_token\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_auth_token\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1796\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1797\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mconfig_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1798\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1800\u001b[0m \u001b[38;5;66;03m# Return iterable dataset in case of streaming\u001b[39;00m\n\u001b[1;32m   1801\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m streaming:\n",
       "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1514\u001b[0m, in \u001b[0;36mload_dataset_builder\u001b[0;34m(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, storage_options, **config_kwargs)\u001b[0m\n\u001b[1;32m   1512\u001b[0m     download_config \u001b[38;5;241m=\u001b[39m download_config\u001b[38;5;241m.\u001b[39mcopy() \u001b[38;5;28;01mif\u001b[39;00m download_config \u001b[38;5;28;01melse\u001b[39;00m DownloadConfig()\n\u001b[1;32m   1513\u001b[0m     download_config\u001b[38;5;241m.\u001b[39muse_auth_token \u001b[38;5;241m=\u001b[39m use_auth_token\n\u001b[0;32m-> 1514\u001b[0m dataset_module \u001b[38;5;241m=\u001b[39m \u001b[43mdataset_module_factory\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1515\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1516\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1517\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1518\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1519\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1520\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1521\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1523\u001b[0m \u001b[38;5;66;03m# Get dataset builder class from the processing script\u001b[39;00m\n\u001b[1;32m   1524\u001b[0m builder_cls \u001b[38;5;241m=\u001b[39m import_main_class(dataset_module\u001b[38;5;241m.\u001b[39mmodule_path)\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1165\u001b[0m, in \u001b[0;36mdataset_module_factory\u001b[0;34m(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)\u001b[0m\n\u001b[1;32m   1159\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m LocalDatasetModuleFactoryWithScript(\n\u001b[1;32m   1160\u001b[0m         combined_path, download_mode\u001b[38;5;241m=\u001b[39mdownload_mode, dynamic_modules_path\u001b[38;5;241m=\u001b[39mdynamic_modules_path\n\u001b[1;32m   1161\u001b[0m     )\u001b[38;5;241m.\u001b[39mget_module()\n\u001b[1;32m   1162\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39misdir(path):\n\u001b[1;32m   1163\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mLocalDatasetModuleFactoryWithoutScript\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1164\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\n\u001b[0;32m-> 1165\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_module\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1166\u001b[0m \u001b[38;5;66;03m# Try remotely\u001b[39;00m\n\u001b[1;32m   1167\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m is_relative_path(path) \u001b[38;5;129;01mand\u001b[39;00m path\u001b[38;5;241m.\u001b[39mcount(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m:\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:642\u001b[0m, in \u001b[0;36mLocalDatasetModuleFactoryWithoutScript.get_module\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    638\u001b[0m base_path \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpath, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_dir) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_dir \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpath\n\u001b[1;32m    639\u001b[0m patterns \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m    640\u001b[0m     sanitize_patterns(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_files) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_files \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m get_data_patterns_locally(base_path)\n\u001b[1;32m    641\u001b[0m )\n\u001b[0;32m--> 642\u001b[0m data_files \u001b[38;5;241m=\u001b[39m \u001b[43mDataFilesDict\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_local_or_remote\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    643\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpatterns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    644\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbase_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    645\u001b[0m \u001b[43m    \u001b[49m\u001b[43mallowed_extensions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mALL_ALLOWED_EXTENSIONS\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    646\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    647\u001b[0m split_modules \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m    648\u001b[0m     split: infer_module_for_data_files(data_files_list) \u001b[38;5;28;01mfor\u001b[39;00m split, data_files_list \u001b[38;5;129;01min\u001b[39;00m data_files\u001b[38;5;241m.\u001b[39mitems()\n\u001b[1;32m    649\u001b[0m }\n\u001b[1;32m    650\u001b[0m module_name, builder_kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mnext\u001b[39m(\u001b[38;5;28miter\u001b[39m(split_modules\u001b[38;5;241m.\u001b[39mvalues()))\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/data_files.py:792\u001b[0m, in \u001b[0;36mDataFilesDict.from_local_or_remote\u001b[0;34m(cls, patterns, base_path, allowed_extensions, use_auth_token)\u001b[0m\n\u001b[1;32m    789\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mcls\u001b[39m()\n\u001b[1;32m    790\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m key, patterns_for_key \u001b[38;5;129;01min\u001b[39;00m patterns\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m    791\u001b[0m     out[key] \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 792\u001b[0m         \u001b[43mDataFilesList\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_local_or_remote\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    793\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpatterns_for_key\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    794\u001b[0m \u001b[43m            \u001b[49m\u001b[43mbase_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    795\u001b[0m \u001b[43m            \u001b[49m\u001b[43mallowed_extensions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallowed_extensions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    796\u001b[0m \u001b[43m            \u001b[49m\u001b[43muse_auth_token\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_auth_token\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    797\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    798\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(patterns_for_key, DataFilesList)\n\u001b[1;32m    799\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m patterns_for_key\n\u001b[1;32m    800\u001b[0m     )\n\u001b[1;32m    801\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/data_files.py:748\u001b[0m, in \u001b[0;36mDataFilesList.from_local_or_remote\u001b[0;34m(cls, patterns, base_path, allowed_extensions, use_auth_token)\u001b[0m\n\u001b[1;32m    739\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m    740\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_local_or_remote\u001b[39m(\n\u001b[1;32m    741\u001b[0m     \u001b[38;5;28mcls\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    745\u001b[0m     use_auth_token: Optional[Union[\u001b[38;5;28mbool\u001b[39m, \u001b[38;5;28mstr\u001b[39m]] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    746\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDataFilesList\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    747\u001b[0m     base_path \u001b[38;5;241m=\u001b[39m base_path \u001b[38;5;28;01mif\u001b[39;00m base_path \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mstr\u001b[39m(Path()\u001b[38;5;241m.\u001b[39mresolve())\n\u001b[0;32m--> 748\u001b[0m     data_files \u001b[38;5;241m=\u001b[39m \u001b[43mresolve_patterns_locally_or_by_urls\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbase_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpatterns\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mallowed_extensions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    749\u001b[0m     origin_metadata \u001b[38;5;241m=\u001b[39m _get_origin_metadata_locally_or_by_urls(data_files, use_auth_token\u001b[38;5;241m=\u001b[39muse_auth_token)\n\u001b[1;32m    750\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(data_files, origin_metadata)\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/data_files.py:355\u001b[0m, in \u001b[0;36mresolve_patterns_locally_or_by_urls\u001b[0;34m(base_path, patterns, allowed_extensions)\u001b[0m\n\u001b[1;32m    353\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m allowed_extensions \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    354\u001b[0m         error_msg \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m with any supported extension \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlist\u001b[39m(allowed_extensions)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 355\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(error_msg)\n\u001b[1;32m    356\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m data_files\n",
-      "\u001b[0;31mFileNotFoundError\u001b[0m: Unable to resolve any data file that matches '['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**']' at /var/cr06_data/jue@together.xyz/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']"
+      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1227\u001b[0m, in \u001b[0;36mdataset_module_factory\u001b[0;34m(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)\u001b[0m\n\u001b[1;32m   1225\u001b[0m                 \u001b[38;5;28;01mraise\u001b[39;00m e1 \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1226\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e1, \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m):\n\u001b[0;32m-> 1227\u001b[0m                 \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\n\u001b[1;32m   1228\u001b[0m                     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCouldn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt find a dataset script at \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mrelative_to_absolute_path(combined_path)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m or any data file in the same directory. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1229\u001b[0m                     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCouldn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt find \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m on the Hugging Face Hub either: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(e1)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00me1\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1230\u001b[0m                 ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1231\u001b[0m             \u001b[38;5;28;01mraise\u001b[39;00m e1 \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1232\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: Couldn't find a dataset script at /var/cr06_data/jue@together.xyz/target-data/notebooks/juewang/target-data/target-data.py or any data file in the same directory. Couldn't find 'juewang/target-data' on the Hugging Face Hub either: FileNotFoundError: Unable to resolve any data file that matches ['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**'] in dataset repository juewang/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']"
      ]
     }
    ],
    "source": [
-    "data = load_dataset('../')"
+    "data = load_dataset('juewang/target-data', split='train')"
    ]
   },
   {

notebooks/convert-lm-eval-harness.ipynb

@@ -33,7 +33,7 @@
     "task_name = 'hellaswag'\n",
     "data = load_dataset(task_name)\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        text = item['ctx'] + item['endings'][int(item['label'])]\n",
     "        f.write(\n",
@@ -62,7 +62,7 @@
     "task_name = 'boolq'\n",
     "data = load_dataset(task_name)\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        text = f\"{item['passage']}\\nQuestion: {item['question']}?\\nAnswer: {item['answer']}\"\n",
     "        f.write(\n",
@@ -119,7 +119,7 @@
     "task_name = 'arc_challenge'\n",
     "data = load_dataset('ai2_arc', 'ARC-Challenge')\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        i_a = item['choices']['label'].index(item['answerKey'])\n",
     "        q = item['question']\n",
@@ -169,7 +169,7 @@
     "task_name = 'arc_easy'\n",
     "data = load_dataset('ai2_arc', 'ARC-Easy')\n",
     "data.shuffle(seed=42)\n",
-    "with open(f'../data/{task_name}.jsonl', 'w') as f:\n",
+    "with open(f'../train/{task_name}.jsonl', 'w') as f:\n",
     "    for i_item, item in enumerate(data['train']):\n",
     "        i_a = item['choices']['label'].index(item['answerKey'])\n",
     "        q = item['question']\n",
@@ -182,31 +182,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 17,
    "id": "b3b98d73-4729-40a1-a5ea-51a3bcfd7ffe",
    "metadata": {},
    "outputs": [
     {
      "ename": "FileNotFoundError",
-     "evalue": "Unable to resolve any data file that matches '['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**']' at /var/cr06_data/jue@together.xyz/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']",
+     "evalue": "Couldn't find a dataset script at /var/cr06_data/jue@together.xyz/target-data/notebooks/juewang/target-data/target-data.py or any data file in the same directory. Couldn't find 'juewang/target-data' on the Hugging Face Hub either: FileNotFoundError: Unable to resolve any data file that matches ['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**'] in dataset repository juewang/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']",
      "output_type": "error",
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m../\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "Cell \u001b[0;32mIn[17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mjuewang/target-data\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msplit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtrain\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1785\u001b[0m, in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, storage_options, **config_kwargs)\u001b[0m\n\u001b[1;32m   1780\u001b[0m verification_mode \u001b[38;5;241m=\u001b[39m VerificationMode(\n\u001b[1;32m   1781\u001b[0m     (verification_mode \u001b[38;5;129;01mor\u001b[39;00m VerificationMode\u001b[38;5;241m.\u001b[39mBASIC_CHECKS) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m save_infos \u001b[38;5;28;01melse\u001b[39;00m VerificationMode\u001b[38;5;241m.\u001b[39mALL_CHECKS\n\u001b[1;32m   1782\u001b[0m )\n\u001b[1;32m   1784\u001b[0m \u001b[38;5;66;03m# Create a dataset builder\u001b[39;00m\n\u001b[0;32m-> 1785\u001b[0m builder_instance \u001b[38;5;241m=\u001b[39m \u001b[43mload_dataset_builder\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1786\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1787\u001b[0m \u001b[43m    \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1788\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1789\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1790\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1791\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfeatures\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfeatures\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1792\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1793\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1794\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1795\u001b[0m \u001b[43m    \u001b[49m\u001b[43muse_auth_token\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_auth_token\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1796\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1797\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mconfig_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1798\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1800\u001b[0m \u001b[38;5;66;03m# Return iterable dataset in case of streaming\u001b[39;00m\n\u001b[1;32m   1801\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m streaming:\n",
       "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1514\u001b[0m, in \u001b[0;36mload_dataset_builder\u001b[0;34m(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, storage_options, **config_kwargs)\u001b[0m\n\u001b[1;32m   1512\u001b[0m     download_config \u001b[38;5;241m=\u001b[39m download_config\u001b[38;5;241m.\u001b[39mcopy() \u001b[38;5;28;01mif\u001b[39;00m download_config \u001b[38;5;28;01melse\u001b[39;00m DownloadConfig()\n\u001b[1;32m   1513\u001b[0m     download_config\u001b[38;5;241m.\u001b[39muse_auth_token \u001b[38;5;241m=\u001b[39m use_auth_token\n\u001b[0;32m-> 1514\u001b[0m dataset_module \u001b[38;5;241m=\u001b[39m \u001b[43mdataset_module_factory\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1515\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1516\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrevision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1517\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1518\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1519\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1520\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1521\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1523\u001b[0m \u001b[38;5;66;03m# Get dataset builder class from the processing script\u001b[39;00m\n\u001b[1;32m   1524\u001b[0m builder_cls \u001b[38;5;241m=\u001b[39m import_main_class(dataset_module\u001b[38;5;241m.\u001b[39mmodule_path)\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1165\u001b[0m, in \u001b[0;36mdataset_module_factory\u001b[0;34m(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)\u001b[0m\n\u001b[1;32m   1159\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m LocalDatasetModuleFactoryWithScript(\n\u001b[1;32m   1160\u001b[0m         combined_path, download_mode\u001b[38;5;241m=\u001b[39mdownload_mode, dynamic_modules_path\u001b[38;5;241m=\u001b[39mdynamic_modules_path\n\u001b[1;32m   1161\u001b[0m     )\u001b[38;5;241m.\u001b[39mget_module()\n\u001b[1;32m   1162\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39misdir(path):\n\u001b[1;32m   1163\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mLocalDatasetModuleFactoryWithoutScript\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1164\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_dir\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata_files\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_files\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdownload_mode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdownload_mode\u001b[49m\n\u001b[0;32m-> 1165\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_module\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1166\u001b[0m \u001b[38;5;66;03m# Try remotely\u001b[39;00m\n\u001b[1;32m   1167\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m is_relative_path(path) \u001b[38;5;129;01mand\u001b[39;00m path\u001b[38;5;241m.\u001b[39mcount(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m:\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:642\u001b[0m, in \u001b[0;36mLocalDatasetModuleFactoryWithoutScript.get_module\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    638\u001b[0m base_path \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpath, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_dir) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_dir \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpath\n\u001b[1;32m    639\u001b[0m patterns \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m    640\u001b[0m     sanitize_patterns(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_files) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata_files \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m get_data_patterns_locally(base_path)\n\u001b[1;32m    641\u001b[0m )\n\u001b[0;32m--> 642\u001b[0m data_files \u001b[38;5;241m=\u001b[39m \u001b[43mDataFilesDict\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_local_or_remote\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    643\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpatterns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    644\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbase_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    645\u001b[0m \u001b[43m    \u001b[49m\u001b[43mallowed_extensions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mALL_ALLOWED_EXTENSIONS\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    646\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    647\u001b[0m split_modules \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m    648\u001b[0m     split: infer_module_for_data_files(data_files_list) \u001b[38;5;28;01mfor\u001b[39;00m split, data_files_list \u001b[38;5;129;01min\u001b[39;00m data_files\u001b[38;5;241m.\u001b[39mitems()\n\u001b[1;32m    649\u001b[0m }\n\u001b[1;32m    650\u001b[0m module_name, builder_kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mnext\u001b[39m(\u001b[38;5;28miter\u001b[39m(split_modules\u001b[38;5;241m.\u001b[39mvalues()))\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/data_files.py:792\u001b[0m, in \u001b[0;36mDataFilesDict.from_local_or_remote\u001b[0;34m(cls, patterns, base_path, allowed_extensions, use_auth_token)\u001b[0m\n\u001b[1;32m    789\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mcls\u001b[39m()\n\u001b[1;32m    790\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m key, patterns_for_key \u001b[38;5;129;01min\u001b[39;00m patterns\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m    791\u001b[0m     out[key] \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 792\u001b[0m         \u001b[43mDataFilesList\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_local_or_remote\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    793\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpatterns_for_key\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    794\u001b[0m \u001b[43m            \u001b[49m\u001b[43mbase_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    795\u001b[0m \u001b[43m            \u001b[49m\u001b[43mallowed_extensions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallowed_extensions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    796\u001b[0m \u001b[43m            \u001b[49m\u001b[43muse_auth_token\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_auth_token\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    797\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    798\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(patterns_for_key, DataFilesList)\n\u001b[1;32m    799\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m patterns_for_key\n\u001b[1;32m    800\u001b[0m     )\n\u001b[1;32m    801\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/data_files.py:748\u001b[0m, in \u001b[0;36mDataFilesList.from_local_or_remote\u001b[0;34m(cls, patterns, base_path, allowed_extensions, use_auth_token)\u001b[0m\n\u001b[1;32m    739\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m    740\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_local_or_remote\u001b[39m(\n\u001b[1;32m    741\u001b[0m     \u001b[38;5;28mcls\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    745\u001b[0m     use_auth_token: Optional[Union[\u001b[38;5;28mbool\u001b[39m, \u001b[38;5;28mstr\u001b[39m]] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    746\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDataFilesList\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    747\u001b[0m     base_path \u001b[38;5;241m=\u001b[39m base_path \u001b[38;5;28;01mif\u001b[39;00m base_path \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mstr\u001b[39m(Path()\u001b[38;5;241m.\u001b[39mresolve())\n\u001b[0;32m--> 748\u001b[0m     data_files \u001b[38;5;241m=\u001b[39m \u001b[43mresolve_patterns_locally_or_by_urls\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbase_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpatterns\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mallowed_extensions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    749\u001b[0m     origin_metadata \u001b[38;5;241m=\u001b[39m _get_origin_metadata_locally_or_by_urls(data_files, use_auth_token\u001b[38;5;241m=\u001b[39muse_auth_token)\n\u001b[1;32m    750\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(data_files, origin_metadata)\n",
-      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/data_files.py:355\u001b[0m, in \u001b[0;36mresolve_patterns_locally_or_by_urls\u001b[0;34m(base_path, patterns, allowed_extensions)\u001b[0m\n\u001b[1;32m    353\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m allowed_extensions \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    354\u001b[0m         error_msg \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m with any supported extension \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlist\u001b[39m(allowed_extensions)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 355\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(error_msg)\n\u001b[1;32m    356\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m data_files\n",
-      "\u001b[0;31mFileNotFoundError\u001b[0m: Unable to resolve any data file that matches '['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**']' at /var/cr06_data/jue@together.xyz/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']"
+      "File \u001b[0;32m~/miniconda3/envs/nebula-fav2/lib/python3.10/site-packages/datasets/load.py:1227\u001b[0m, in \u001b[0;36mdataset_module_factory\u001b[0;34m(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)\u001b[0m\n\u001b[1;32m   1225\u001b[0m                 \u001b[38;5;28;01mraise\u001b[39;00m e1 \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1226\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(e1, \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m):\n\u001b[0;32m-> 1227\u001b[0m                 \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\n\u001b[1;32m   1228\u001b[0m                     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCouldn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt find a dataset script at \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mrelative_to_absolute_path(combined_path)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m or any data file in the same directory. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1229\u001b[0m                     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCouldn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt find \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m on the Hugging Face Hub either: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(e1)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00me1\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1230\u001b[0m                 ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1231\u001b[0m             \u001b[38;5;28;01mraise\u001b[39;00m e1 \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1232\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: Couldn't find a dataset script at /var/cr06_data/jue@together.xyz/target-data/notebooks/juewang/target-data/target-data.py or any data file in the same directory. Couldn't find 'juewang/target-data' on the Hugging Face Hub either: FileNotFoundError: Unable to resolve any data file that matches ['test[-._ 0-9/]**', '**[-._ 0-9/]test[-._ 0-9/]**', 'testing[-._ 0-9/]**', '**[-._ 0-9/]testing[-._ 0-9/]**', 'eval[-._ 0-9/]**', '**[-._ 0-9/]eval[-._ 0-9/]**', 'evaluation[-._ 0-9/]**', '**[-._ 0-9/]evaluation[-._ 0-9/]**'] in dataset repository juewang/target-data with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.arrow', '.txt', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']"
      ]
     }
    ],
    "source": [
-    "data = load_dataset('../')"
+    "data = load_dataset('juewang/target-data', split='train')"
    ]
   },
   {