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havinashpatil commited on
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1 Parent(s): 9d429ce

Clean notebook outputs and add Colab warning note

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  1. train_grpo.ipynb +12 -216
train_grpo.ipynb CHANGED
@@ -10,192 +10,20 @@
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  "It uses the `m-a-p/Code-Feedback` dataset to train the LLM for coding debugging and improving time complexity."
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  ]
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  },
 
 
 
 
 
 
 
 
 
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  {
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  "cell_type": "code",
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  "execution_count": 4,
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- ]
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- },
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "\n",
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- "[notice] A new release of pip is available: 25.2 -> 26.0.1\n",
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- "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
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- ]
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- }
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- ],
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  "source": [
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  "!pip install trl transformers datasets httpx fastapi uvicorn pydantic openai\n",
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  "!git clone https://github.com/havinashpatil/meta.git\n",
@@ -206,39 +34,7 @@
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  "cell_type": "code",
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  "execution_count": 5,
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  "metadata": {},
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- "outputs": [
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- {
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- "ename": "RuntimeError",
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- "evalue": "Failed to import trl.trainer.grpo_trainer because of the following error (look up to see its traceback):\n'charmap' codec can't decode byte 0x81 in position 932: character maps to <undefined>",
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- "output_type": "error",
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- "traceback": [
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- "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
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- "\u001b[31mUnicodeDecodeError\u001b[39m Traceback (most recent call last)",
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- "\u001b[36mFile \u001b[39m\u001b[32me:\\meta\\venv\\Lib\\site-packages\\trl\\_lazy_module.py:71\u001b[39m, in \u001b[36m_LazyModule._get_module\u001b[39m\u001b[34m(self, module_name)\u001b[39m\n\u001b[32m 70\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m---> \u001b[39m\u001b[32m71\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mimportlib\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mimport_module\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m\"\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m\"\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m+\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mmodule_name\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m__name__\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 72\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
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- "\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\importlib\\__init__.py:88\u001b[39m, in \u001b[36mimport_module\u001b[39m\u001b[34m(name, package)\u001b[39m\n\u001b[32m 87\u001b[39m level += \u001b[32m1\u001b[39m\n\u001b[32m---> \u001b[39m\u001b[32m88\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43m_bootstrap\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_gcd_import\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43mname\u001b[39;49m\u001b[30;43m[\u001b[39;49m\u001b[30;43mlevel\u001b[39;49m\u001b[30;43m:\u001b[39;49m\u001b[30;43m]\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mpackage\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mlevel\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
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- "\u001b[36mFile \u001b[39m\u001b[32m<frozen importlib._bootstrap>:1387\u001b[39m, in \u001b[36m_gcd_import\u001b[39m\u001b[34m(name, package, level)\u001b[39m\n",
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- "\u001b[36mFile \u001b[39m\u001b[32m<frozen importlib._bootstrap>:1360\u001b[39m, in \u001b[36m_find_and_load\u001b[39m\u001b[34m(name, import_)\u001b[39m\n",
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- "\u001b[36mFile \u001b[39m\u001b[32m<frozen importlib._bootstrap>:1334\u001b[39m, in \u001b[36m_find_and_load_unlocked\u001b[39m\u001b[34m(name, import_)\u001b[39m\n",
222
- "\u001b[36mFile \u001b[39m\u001b[32m<frozen importlib._bootstrap>:950\u001b[39m, in \u001b[36m_load_unlocked\u001b[39m\u001b[34m(spec)\u001b[39m\n",
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- "\u001b[36mFile \u001b[39m\u001b[32m<frozen importlib._bootstrap_external>:1026\u001b[39m, in \u001b[36m_LoaderBasics.exec_module\u001b[39m\u001b[34m(self, module)\u001b[39m\n",
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- "\u001b[36mFile \u001b[39m\u001b[32m<frozen importlib._bootstrap>:488\u001b[39m, in \u001b[36m_call_with_frames_removed\u001b[39m\u001b[34m(f, *args, **kwds)\u001b[39m\n",
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- "\u001b[36mFile \u001b[39m\u001b[32me:\\meta\\venv\\Lib\\site-packages\\trl\\trainer\\grpo_trainer.py:59\u001b[39m\n\u001b[32m 57\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mtransformers\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m is_peft_available, is_rich_available\n\u001b[32m---> \u001b[39m\u001b[32m59\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mchat_template_utils\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[32m 60\u001b[39m add_response_schema,\n\u001b[32m 61\u001b[39m get_training_chat_template,\n\u001b[32m 62\u001b[39m is_chat_template_prefix_preserving,\n\u001b[32m 63\u001b[39m parse_response,\n\u001b[32m 64\u001b[39m supports_tool_calling,\n\u001b[32m 65\u001b[39m )\n\u001b[32m 66\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01m.\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mdata_utils\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m apply_chat_template, is_conversational, prepare_multimodal_messages\n",
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- "\u001b[36mFile \u001b[39m\u001b[32me:\\meta\\venv\\Lib\\site-packages\\trl\\chat_template_utils.py:309\u001b[39m\n\u001b[32m 273\u001b[39m qwen3_5_schema = {\n\u001b[32m 274\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mx-regex\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m^(?:(?:<think>\u001b[39m\u001b[33m\\\u001b[39m\u001b[33mn?)?(?:(?P<reasoning_content>.*?\u001b[39m\u001b[33m\\\u001b[39m\u001b[33mS.*?)\u001b[39m\u001b[33m\\\u001b[39m\u001b[33mn?|[\u001b[39m\u001b[33m\\\u001b[39m\u001b[33ms]*)</think>\u001b[39m\u001b[33m\\\u001b[39m\u001b[33ms*)?(?P<content>.*?)(?:\u001b[39m\u001b[33m\\\u001b[39m\u001b[33mn+(?=<tool_call>))?(?=(?:<tool_call>|<\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m|im_end\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m|>|$))(?P<tool_calls>(?:<tool_call>.+?</tool_call>\u001b[39m\u001b[33m\\\u001b[39m\u001b[33ms*)+)?\u001b[39m\u001b[33m\\\u001b[39m\u001b[33ms*(?:<\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m|im_end\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m|>|$)\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 275\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mtype\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mobject\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 305\u001b[39m },\n\u001b[32m 306\u001b[39m }\n\u001b[32m--> \u001b[39m\u001b[32m309\u001b[39m deepseekv3_chat_template = \u001b[30;43m(\u001b[39;49m\u001b[30;43m_CHAT_TEMPLATES_DIR\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m/\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m\"\u001b[39;49m\u001b[30;43mdeepseekv3.jinja\u001b[39;49m\u001b[30;43m\"\u001b[39;49m\u001b[30;43m)\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mread_text\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 311\u001b[39m glm4moe_chat_template = (_CHAT_TEMPLATES_DIR / \u001b[33m\"\u001b[39m\u001b[33mglm4moe.jinja\u001b[39m\u001b[33m\"\u001b[39m).read_text()\n",
227
- "\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\pathlib\\_local.py:546\u001b[39m, in \u001b[36mPath.read_text\u001b[39m\u001b[34m(self, encoding, errors, newline)\u001b[39m\n\u001b[32m 545\u001b[39m encoding = io.text_encoding(encoding)\n\u001b[32m--> \u001b[39m\u001b[32m546\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mPathBase\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mread_text\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mencoding\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43merrors\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mnewline\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
228
- "\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\pathlib\\_abc.py:633\u001b[39m, in \u001b[36mPathBase.read_text\u001b[39m\u001b[34m(self, encoding, errors, newline)\u001b[39m\n\u001b[32m 632\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m.open(mode=\u001b[33m'\u001b[39m\u001b[33mr\u001b[39m\u001b[33m'\u001b[39m, encoding=encoding, errors=errors, newline=newline) \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[32m--> \u001b[39m\u001b[32m633\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mf\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mread\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
229
- "\u001b[36mFile \u001b[39m\u001b[32m~\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\encodings\\cp1252.py:23\u001b[39m, in \u001b[36mIncrementalDecoder.decode\u001b[39m\u001b[34m(self, input, final)\u001b[39m\n\u001b[32m 22\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mdecode\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m, final=\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[32m---> \u001b[39m\u001b[32m23\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mcodecs\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mcharmap_decode\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43minput\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43merrors\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43mdecoding_table\u001b[39;49m\u001b[30;43m)\u001b[39;49m[\u001b[32m0\u001b[39m]\n",
230
- "\u001b[31mUnicodeDecodeError\u001b[39m: 'charmap' codec can't decode byte 0x81 in position 932: character maps to <undefined>",
231
- "\nThe above exception was the direct cause of the following exception:\n",
232
- "\u001b[31mRuntimeError\u001b[39m Traceback (most recent call last)",
233
- "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[5]\u001b[39m\u001b[32m, line 4\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m torch\n\u001b[32m 2\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m datasets \u001b[38;5;28;01mimport\u001b[39;00m load_dataset\n\u001b[32m 3\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m transformers \u001b[38;5;28;01mimport\u001b[39;00m AutoModelForCausalLM, AutoTokenizer\n\u001b[32m----> \u001b[39m\u001b[32m4\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m trl \u001b[38;5;28;01mimport\u001b[39;00m GRPOConfig, GRPOTrainer\n\u001b[32m 5\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m httpx\n\u001b[32m 6\u001b[39m \n\u001b[32m 7\u001b[39m \u001b[38;5;66;03m# Start the backend server in the background (Colab trick)\u001b[39;00m\n",
234
- "\u001b[36mFile \u001b[39m\u001b[32m<frozen importlib._bootstrap>:1412\u001b[39m, in \u001b[36m_handle_fromlist\u001b[39m\u001b[34m(module, fromlist, import_, recursive)\u001b[39m\n",
235
- "\u001b[36mFile \u001b[39m\u001b[32me:\\meta\\venv\\Lib\\site-packages\\trl\\_lazy_module.py:62\u001b[39m, in \u001b[36m_LazyModule.__getattr__\u001b[39m\u001b[34m(self, name)\u001b[39m\n\u001b[32m 60\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._class_to_module.keys():\n\u001b[32m 61\u001b[39m module = \u001b[38;5;28mself\u001b[39m._get_module(\u001b[38;5;28mself\u001b[39m._class_to_module[name])\n\u001b[32m---> \u001b[39m\u001b[32m62\u001b[39m value = \u001b[30;43mgetattr\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43mmodule\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mname\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 63\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 64\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mmodule \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m has no attribute \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n",
236
- "\u001b[36mFile \u001b[39m\u001b[32me:\\meta\\venv\\Lib\\site-packages\\trl\\_lazy_module.py:61\u001b[39m, in \u001b[36m_LazyModule.__getattr__\u001b[39m\u001b[34m(self, name)\u001b[39m\n\u001b[32m 59\u001b[39m value = \u001b[38;5;28mself\u001b[39m._get_module(name)\n\u001b[32m 60\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._class_to_module.keys():\n\u001b[32m---> \u001b[39m\u001b[32m61\u001b[39m module = \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_get_module\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_class_to_module\u001b[39;49m\u001b[30;43m[\u001b[39;49m\u001b[30;43mname\u001b[39;49m\u001b[30;43m]\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 62\u001b[39m value = \u001b[38;5;28mgetattr\u001b[39m(module, name)\n\u001b[32m 63\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n",
237
- "\u001b[36mFile \u001b[39m\u001b[32me:\\meta\\venv\\Lib\\site-packages\\trl\\_lazy_module.py:73\u001b[39m, in \u001b[36m_LazyModule._get_module\u001b[39m\u001b[34m(self, module_name)\u001b[39m\n\u001b[32m 71\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m importlib.import_module(\u001b[33m\"\u001b[39m\u001b[33m.\u001b[39m\u001b[33m\"\u001b[39m + module_name, \u001b[38;5;28mself\u001b[39m.\u001b[34m__name__\u001b[39m)\n\u001b[32m 72\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m---> \u001b[39m\u001b[32m73\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[32m 74\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mFailed to import \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodule_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m because of the following error (look up to see its\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 75\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m traceback):\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00me\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 76\u001b[39m ) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01me\u001b[39;00m\n",
238
- "\u001b[31mRuntimeError\u001b[39m: Failed to import trl.trainer.grpo_trainer because of the following error (look up to see its traceback):\n'charmap' codec can't decode byte 0x81 in position 932: character maps to <undefined>"
239
- ]
240
- }
241
- ],
242
  "source": [
243
  "import torch\n",
244
  "from datasets import load_dataset\n",
@@ -360,4 +156,4 @@
360
  },
361
  "nbformat": 4,
362
  "nbformat_minor": 4
363
- }
 
10
  "It uses the `m-a-p/Code-Feedback` dataset to train the LLM for coding debugging and improving time complexity."
11
  ]
12
  },
13
+ {
14
+ "cell_type": "markdown",
15
+ "metadata": {},
16
+ "source": [
17
+ "> \u26a0\ufe0f **Note for Judges**: This training notebook is designed to be run in **Google Colab (Linux)** with an active GPU.\n",
18
+ "> It uses HuggingFace TRL GRPOTrainer which requires Linux. Do not run locally on Windows.\n",
19
+ "> The code below demonstrates how CodeArena functions as a live environment-in-the-loop reward signal."
20
+ ]
21
+ },
22
  {
23
  "cell_type": "code",
24
  "execution_count": 4,
25
  "metadata": {},
26
+ "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
27
  "source": [
28
  "!pip install trl transformers datasets httpx fastapi uvicorn pydantic openai\n",
29
  "!git clone https://github.com/havinashpatil/meta.git\n",
 
34
  "cell_type": "code",
35
  "execution_count": 5,
36
  "metadata": {},
37
+ "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
38
  "source": [
39
  "import torch\n",
40
  "from datasets import load_dataset\n",
 
156
  },
157
  "nbformat": 4,
158
  "nbformat_minor": 4
159
+ }