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AutoTokenizer.from_pretrained(model_path)\n","model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloat16, device_map=\"auto\")\n"]},{"cell_type":"code","source":["from peft import LoraConfig\n","\n","peft_config = LoraConfig(\n","    r=8,\n","    lora_alpha=16,\n","    target_modules=[\"q_proj\", \"v_proj\"],\n","    lora_dropout=0.05,\n","    bias=\"none\",\n","    task_type=\"CAUSAL_LM\"\n",")\n"],"metadata":{"id":"G3sV7C-fO7YM","executionInfo":{"status":"ok","timestamp":1750573249856,"user_tz":-330,"elapsed":10,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":6,"outputs":[]},{"cell_type":"code","source":["pip install datasets\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Zx36Sx6YTG0m","executionInfo":{"status":"ok","timestamp":1750573289824,"user_tz":-330,"elapsed":6829,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"5a64096a-5145-45a6-a110-e8f1b6b2b5f3"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: datasets in /usr/local/lib/python3.11/dist-packages (3.6.0)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from datasets) (3.18.0)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from datasets) (2.0.2)\n","Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (18.1.0)\n","Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.3.7)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from datasets) (2.2.2)\n","Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.11/dist-packages (from datasets) (2.32.3)\n","Requirement already satisfied: tqdm>=4.66.3 in /usr/local/lib/python3.11/dist-packages (from datasets) (4.67.1)\n","Requirement already satisfied: xxhash in /usr/local/lib/python3.11/dist-packages (from datasets) (3.5.0)\n","Requirement already satisfied: multiprocess<0.70.17 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.70.15)\n","Requirement already satisfied: fsspec<=2025.3.0,>=2023.1.0 in /usr/local/lib/python3.11/dist-packages (from fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (2025.3.0)\n","Requirement already satisfied: huggingface-hub>=0.24.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.33.0)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from datasets) (24.2)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from datasets) (6.0.2)\n","Requirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /usr/local/lib/python3.11/dist-packages (from fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (3.11.15)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.24.0->datasets) (4.14.0)\n","Requirement already satisfied: hf-xet<2.0.0,>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.24.0->datasets) (1.1.3)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.4.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.10)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2.4.0)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2025.6.15)\n","Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2.9.0.post0)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2025.2)\n","Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2025.2)\n","Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (2.6.1)\n","Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (1.3.2)\n","Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (25.3.0)\n","Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (1.7.0)\n","Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (6.4.4)\n","Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (0.3.2)\n","Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (1.20.1)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.17.0)\n"]}]},{"cell_type":"code","source":["dataset = load_dataset(\"code_search_net\", \"python\", split=\"train\")"],"metadata":{"id":"EHatovAoUYtb","executionInfo":{"status":"ok","timestamp":1750573646939,"user_tz":-330,"elapsed":5321,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":12,"outputs":[]},{"cell_type":"code","source":["dataset[0]  # show the first example\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"EMlKH8bXP5A5","executionInfo":{"status":"ok","timestamp":1750573665817,"user_tz":-330,"elapsed":38,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"0b4a7b53-07f2-4789-a5d6-93a6ead58634"},"execution_count":13,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'repository_name': 'ArabellaTech/django-basic-cms',\n"," 'func_path_in_repository': 'basic_cms/templatetags/pages_tags.py',\n"," 'func_name': 'show_slug_with_level',\n"," 'whole_func_string': 'def show_slug_with_level(context, page, lang=None, fallback=True):\\n    \"\"\"Display slug with level by language.\"\"\"\\n    if not lang:\\n        lang = context.get(\\'lang\\', pages_settings.PAGE_DEFAULT_LANGUAGE)\\n\\n    page = get_page_from_string_or_id(page, lang)\\n    if not page:\\n        return \\'\\'\\n\\n    return {\\'content\\': page.slug_with_level(lang)}',\n"," 'language': 'python',\n"," 'func_code_string': 'def show_slug_with_level(context, page, lang=None, fallback=True):\\n    \"\"\"Display slug with level by language.\"\"\"\\n    if not lang:\\n        lang = context.get(\\'lang\\', pages_settings.PAGE_DEFAULT_LANGUAGE)\\n\\n    page = get_page_from_string_or_id(page, lang)\\n    if not page:\\n        return \\'\\'\\n\\n    return {\\'content\\': page.slug_with_level(lang)}',\n"," 'func_code_tokens': ['def',\n","  'show_slug_with_level',\n","  '(',\n","  'context',\n","  ',',\n","  'page',\n","  ',',\n","  'lang',\n","  '=',\n","  'None',\n","  ',',\n","  'fallback',\n","  '=',\n","  'True',\n","  ')',\n","  ':',\n","  'if',\n","  'not',\n","  'lang',\n","  ':',\n","  'lang',\n","  '=',\n","  'context',\n","  '.',\n","  'get',\n","  '(',\n","  \"'lang'\",\n","  ',',\n","  'pages_settings',\n","  '.',\n","  'PAGE_DEFAULT_LANGUAGE',\n","  ')',\n","  'page',\n","  '=',\n","  'get_page_from_string_or_id',\n","  '(',\n","  'page',\n","  ',',\n","  'lang',\n","  ')',\n","  'if',\n","  'not',\n","  'page',\n","  ':',\n","  'return',\n","  \"''\",\n","  'return',\n","  '{',\n","  \"'content'\",\n","  ':',\n","  'page',\n","  '.',\n","  'slug_with_level',\n","  '(',\n","  'lang',\n","  ')',\n","  '}'],\n"," 'func_documentation_string': 'Display slug with level by language.',\n"," 'func_documentation_tokens': ['Display',\n","  'slug',\n","  'with',\n","  'level',\n","  'by',\n","  'language',\n","  '.'],\n"," 'split_name': 'train',\n"," 'func_code_url': 'https://github.com/ArabellaTech/django-basic-cms/blob/863f3c6098606f663994930cd8e7723ad0c07caf/basic_cms/templatetags/pages_tags.py#L174-L183'}"]},"metadata":{},"execution_count":13}]},{"cell_type":"code","source":["from datasets import load_dataset, DatasetDict\n","dataset = dataset.shuffle(seed=42)\n","split_dataset = dataset.train_test_split(test_size=0.2)\n","\n","# Optional: split the test set again into val + test\n","split_dataset = DatasetDict({\n","    \"train\": split_dataset[\"train\"],\n","    \"val\": split_dataset[\"test\"].train_test_split(test_size=0.5, seed=42)[\"train\"],\n","    \"test\": split_dataset[\"test\"].train_test_split(test_size=0.5, seed=42)[\"test\"]\n","})"],"metadata":{"id":"okaeh2c3TQB9","executionInfo":{"status":"ok","timestamp":1750574055892,"user_tz":-330,"elapsed":754,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":15,"outputs":[]},{"cell_type":"code","source":["split_dataset[\"train\"]  # 80%\n","split_dataset[\"val\"]    # 10%\n","split_dataset[\"test\"]   # 10%\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xgNQXEVvV9YQ","executionInfo":{"status":"ok","timestamp":1750574072169,"user_tz":-330,"elapsed":40,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"86eb89a5-14d9-430f-b1fd-b0e11386ad6d"},"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Dataset({\n","    features: ['repository_name', 'func_path_in_repository', 'func_name', 'whole_func_string', 'language', 'func_code_string', 'func_code_tokens', 'func_documentation_string', 'func_documentation_tokens', 'split_name', 'func_code_url'],\n","    num_rows: 41218\n","})"]},"metadata":{},"execution_count":16}]},{"cell_type":"code","source":["import random\n","\n","def format_multitask(example):\n","    code = example.get(\"func_code_string\")\n","    doc = example.get(\"func_documentation_string\")\n","\n","    if not code or not doc:\n","        return {\"text\": \"\"}  # skip incomplete samples\n","\n","    first_line = code.splitlines()[0] if code else \"\"\n","\n","    tasks = [\n","        f\"### Instruction:\\nWrite a function for this description:\\n{doc}\\n\\n### Response:\\n{code}\",\n","        f\"### Instruction:\\nExplain what this function does:\\n{code}\\n\\n### Response:\\n{doc}\",\n","        f\"### Instruction:\\nComplete the following function:\\n{first_line}\\n\\n### Response:\\n{code}\",\n","        f\"### Instruction:\\nImprove the readability of this function:\\n{code}\\n\\n### Response:\\n{code}\"\n","    ]\n","\n","    return {\"text\": random.choice(tasks)}\n"],"metadata":{"id":"Z-QXyNf4WIBT","executionInfo":{"status":"ok","timestamp":1750574382130,"user_tz":-330,"elapsed":23,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":21,"outputs":[]},{"cell_type":"code","source":["print(split_dataset[\"train\"].column_names)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Z-1WfN91XHl8","executionInfo":{"status":"ok","timestamp":1750574387832,"user_tz":-330,"elapsed":23,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"faa4559b-3197-40b1-c42d-f28c6940fb4b"},"execution_count":22,"outputs":[{"output_type":"stream","name":"stdout","text":["['repository_name', 'func_path_in_repository', 'func_name', 'whole_func_string', 'language', 'func_code_string', 'func_code_tokens', 'func_documentation_string', 'func_documentation_tokens', 'split_name', 'func_code_url']\n"]}]},{"cell_type":"code","source":["formatted_dataset = split_dataset.map(format_multitask)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":113,"referenced_widgets":["4c9ead68f2d3414f95c83c02b4c6e65c","9c949dd8d9e3419f87c89e484ee591bc","04f0b6c2885e4046ad00b7b29bfd7fa2","62e5078a57294fc08c5cc3a655483d6c","c6db10b589bb473d8ddcd8cdbbee7bee","10a04b3a6fdd48ce83d92a55296b9929","f671d094aef940d2bf5a829d507f2161","b62fd45404554d63832d25cfb20b6895","17005f77d3f641ddaf5ed74981b1ec50","582e8d00aac249d4b7058d6d8ffeba95","0c352c46a5244c1da9c3fd8e93979d2c","52e8c786161a4a109a3d1d4bb2e24da8","e076111cab0443239c11694e2d5e09d9","b308ca4a4fad4de19e9a45bebac2c2b4","28df34e8bbf948179ced99cf0df1346d","fb493c18754b4842a04b4721c6a76897","ec6a232a8c544079a6adb75994fad83e","7cf53975d2294be39ee599d99436614e","e62f8e4d9a824be4938d16da96ad9fa7","fbecba5bb74c4a48af478cec394f1711","cb66b7ac92c1439da51ef49d00c14e59","558c642d58d845258c6547df3849c5f1","7f3af0742df44359be7f399e4860dcd1","c2e65189c97d4b22be414cb5e09dfe67","ef35f5d0ef76487a84161ad1122fb3fc","796d1ea612f54fbdb4360b0f6506a2a1","6152970f0a4f45c8bb10356f96fc6837","60623e0e1d51460cbedcab48941ab1b1","e3bda63c3e3646df93a04175d5f1c5dd","e00b45399d314e8eaf3cd809950333cc","d961955f2131411a8f39695c704ec411","7b05fb5eba1b4d7cb15edbbd0f2c997a","aa219a9f72024040951f017787f42b24"]},"id":"Ky-aEYpiWih2","executionInfo":{"status":"ok","timestamp":1750574516907,"user_tz":-330,"elapsed":122580,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"553b5358-4f88-4dab-e4be-da82144b0501"},"execution_count":23,"outputs":[{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/329742 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"4c9ead68f2d3414f95c83c02b4c6e65c"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/41218 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"52e8c786161a4a109a3d1d4bb2e24da8"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/41218 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7f3af0742df44359be7f399e4860dcd1"}},"metadata":{}}]},{"cell_type":"code","source":["from datasets import DatasetDict\n","\n","formatted_dataset = DatasetDict({\n","    split: formatted_dataset[split].remove_columns(\n","        [col for col in formatted_dataset[split].column_names if col != \"text\"]\n","    )\n","    for split in formatted_dataset\n","})\n"],"metadata":{"id":"E_OfqtV0WoTJ","executionInfo":{"status":"ok","timestamp":1750574522215,"user_tz":-330,"elapsed":4,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":24,"outputs":[]},{"cell_type":"code","source":["print(formatted_dataset[\"train\"][0][\"text\"])\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"dcpiJ3knXnEU","executionInfo":{"status":"ok","timestamp":1750574525631,"user_tz":-330,"elapsed":25,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"5b4d99f3-2d79-44c6-d245-2b6056db3004"},"execution_count":25,"outputs":[{"output_type":"stream","name":"stdout","text":["### Instruction:\n","Write a function for this description:\n","set general brightness in range 0...1\n","\n","### Response:\n","def set_brightness(self, brightness):\n","        \"\"\"set general brightness in range 0...1\"\"\"\n","        brightness = min([1.0, max([brightness, 0.0])]) # enforces range 0 ... 1\n","        self.state.brightness = brightness\n","        self._repeat_last_frame()\n","        sequence_number = self.zmq_publisher.publish_brightness(brightness)\n","        logging.debug(\"Set brightness to {brightPercent:05.1f}%\".format(brightPercent=brightness*100))\n","        return (True, sequence_number, \"OK\")\n"]}]},{"cell_type":"code","source":["from transformers import AutoTokenizer\n","\n","model_path = \"bigcode/starcoder2-3b\"\n","tokenizer = AutoTokenizer.from_pretrained(model_path)\n","tokenizer.pad_token = tokenizer.eos_token\n","\n","\n","def tokenize(example):\n","    return tokenizer(\n","        example[\"text\"],\n","        truncation=True,\n","        padding=\"max_length\",\n","        max_length=1024  # or 2048 if you're feeling adventurous\n","    )\n","\n","tokenized_dataset = formatted_dataset.map(tokenize, batched=True)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":113,"referenced_widgets":["60d1b664b8dd430c8e6b541d10e822bd","208e4d16085b4b66b12ecd2cab1d0ae3","e8110f004ab84de98a5770250813d031","0ffc8107a39f4a87acc72ff05ded74f6","5b49108636f64d349eee0bdd1c3a19b0","d0892e7174a0464b8f7ace70cac6b879","ea43aaff42824661bd445526b4cf46fd","f0e72586dbdf409fbcfb949d4e66505f","66ec9ef8b2f84e51be677b4f8279c010","4c58607c7fab4cdb8acdff0e265928d4","0f94473a87114d32aab576d08e9ebb77","677258adf4224ed897e5154d30569665","983924e6be564becae8517b16966ea50","e5c88d07287c4667a1790eed8b16e0fd","1176336d88a342149060dbb91aa5e73f","1788b3533c0f495daed87605a7838cdd","123187d563c44058a1f3d9719ae53443","3beb04394c6248ab901c58686e1e04af","81a6306289314a518ec698825a56fa32","2cc8b1d3add249df9f5f94a8e344da21","05d439057a5e4ebcad14d6f743f45664","d32dafdafe704279aa1fe34c544cc83a","df5c5da52f0849c1affc6f242bdaa9bb","206f6f9e708b4449afa70abddb6c3d91","c8db57ef46d94a77a726b76efad9705f","52279871cc0c4ae195a2d4dc4024ae01","c69b6870f37f4c80aa9c0bdde6b2873a","6391e66d82774b418d7c944d0e1ba88e","83cdde8383f8492f9c0b48ca9f53948d","2e62666aad7b4df18bcd2d78bf357864","307fb91652f141759366bd67319cea9d","da480f93f4aa4f22813046c030fec940","c7b43695e6df44e8aa9784c62a04d998"]},"id":"8sYCNTfQX2vA","executionInfo":{"status":"ok","timestamp":1750575261782,"user_tz":-330,"elapsed":556577,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"21651ac2-3501-4e87-80d9-4f16f65dc6e6"},"execution_count":27,"outputs":[{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/329742 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"60d1b664b8dd430c8e6b541d10e822bd"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/41218 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"677258adf4224ed897e5154d30569665"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/41218 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"df5c5da52f0849c1affc6f242bdaa9bb"}},"metadata":{}}]},{"cell_type":"code","source":["print(tokenizer.pad_token, tokenizer.pad_token_id)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mPflARphYJ4v","executionInfo":{"status":"ok","timestamp":1750575315480,"user_tz":-330,"elapsed":54,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"dde27649-76f1-4bdd-d6ab-9783c8882dd5"},"execution_count":28,"outputs":[{"output_type":"stream","name":"stdout","text":["<|endoftext|> 0\n"]}]},{"cell_type":"code","source":["small_tokenized_dataset = DatasetDict({\n","    split: tokenized_dataset[split].select(range(min(len(tokenized_dataset[split]), size)))\n","    for split, size in {\"train\": 1000, \"val\": 200, \"test\": 200}.items()\n","})\n"],"metadata":{"id":"5rxYt74La3j8","executionInfo":{"status":"ok","timestamp":1750575396053,"user_tz":-330,"elapsed":36,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":29,"outputs":[]},{"cell_type":"code","source":["print(tokenizer.pad_token, tokenizer.pad_token_id)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"8bZ0zxpGblHo","executionInfo":{"status":"ok","timestamp":1750575563278,"user_tz":-330,"elapsed":27,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"72342824-04fc-456b-86ca-2e0e20725871"},"execution_count":31,"outputs":[{"output_type":"stream","name":"stdout","text":["<|endoftext|> 0\n"]}]},{"cell_type":"code","source":["print(small_tokenized_dataset[\"train\"][0][\"input_ids\"])\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"DGtqNJ7rcHX3","executionInfo":{"status":"ok","timestamp":1750575644432,"user_tz":-330,"elapsed":11,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"e64a355e-e813-49f9-84ab-ad868a82bbb9"},"execution_count":32,"outputs":[{"output_type":"stream","name":"stdout","text":["[1502, 21052, 63, 222, 2553, 331, 686, 456, 477, 3066, 63, 222, 489, 8108, 29331, 347, 2189, 244, 53, 1198, 54, 222, 222, 1502, 5178, 63, 222, 610, 758, 100, 29057, 45, 803, 49, 29331, 731, 310, 1547, 489, 8108, 29331, 347, 2189, 244, 53, 1198, 54, 3012, 310, 29331, 299, 1865, 2034, 54, 51, 53, 49, 1788, 2034, 29057, 49, 244, 53, 51, 53, 1156, 1156, 607, 949, 39186, 2189, 244, 53, 2437, 244, 54, 310, 649, 51, 1311, 51, 29057, 299, 29331, 310, 649, 1132, 8116, 100, 2153, 100, 1763, 365, 310, 6645, 100, 2188, 299, 649, 51, 47001, 100, 15076, 51, 7226, 100, 29057, 45, 29057, 46, 310, 5751, 51, 2824, 459, 903, 29331, 391, 320, 28838, 12270, 63, 53, 58, 51, 54, 107, 16242, 2316, 1664, 45, 28838, 12270, 66, 29057, 47, 54, 53, 53, 509, 310, 461, 327, 1844, 49, 6645, 100, 2188, 49, 332, 2966, 678, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n"]}]},{"cell_type":"code","source":["pip install --upgrade transformers\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0lc10VnDcz9h","executionInfo":{"status":"ok","timestamp":1750575835355,"user_tz":-330,"elapsed":7376,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"00b78e82-2541-41ad-e8a6-a588bc231971"},"execution_count":33,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: transformers in /usr/local/lib/python3.11/dist-packages (4.52.4)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from transformers) (3.18.0)\n","Requirement already satisfied: huggingface-hub<1.0,>=0.30.0 in /usr/local/lib/python3.11/dist-packages (from transformers) (0.33.0)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from transformers) (2.0.2)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.11/dist-packages (from transformers) (24.2)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from transformers) (6.0.2)\n","Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.11/dist-packages (from transformers) (2024.11.6)\n","Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from transformers) (2.32.3)\n","Requirement already satisfied: tokenizers<0.22,>=0.21 in /usr/local/lib/python3.11/dist-packages (from transformers) (0.21.1)\n","Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.11/dist-packages (from transformers) (0.5.3)\n","Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.11/dist-packages (from transformers) (4.67.1)\n","Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (2025.3.0)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (4.14.0)\n","Requirement already satisfied: hf-xet<2.0.0,>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (1.1.3)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (3.4.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (3.10)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (2.4.0)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->transformers) (2025.6.15)\n"]}]},{"cell_type":"code","source":["import transformers\n","print(transformers.__version__)  # should be >= 4.40\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"90Xi1Dzxc4kj","executionInfo":{"status":"ok","timestamp":1750575868018,"user_tz":-330,"elapsed":41,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"ce24b670-d579-4780-c4ef-a8f207db333d"},"execution_count":34,"outputs":[{"output_type":"stream","name":"stdout","text":["4.52.4\n"]}]},{"cell_type":"code","source":["from transformers import TrainingArguments\n","\n","training_args = TrainingArguments(\n","    output_dir=\"./codex-finetune\",\n","    label_names=[\"input_ids\"],\n","    per_device_train_batch_size=1,\n","    per_device_eval_batch_size=1,\n","    num_train_epochs=3,\n","    logging_dir=\"./logs\",\n","    save_steps=100,\n","    save_total_limit=2,\n","    fp16=True,\n","    gradient_checkpointing=True,\n","    learning_rate=2e-4,\n",")\n"],"metadata":{"id":"bzPediMcdEb3","executionInfo":{"status":"ok","timestamp":1750576628320,"user_tz":-330,"elapsed":56,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":49,"outputs":[]},{"cell_type":"code","source":["from transformers import Trainer, DataCollatorForLanguageModeling\n","\n","# Collator for Causal LM\n","data_collator = DataCollatorForLanguageModeling(\n","    tokenizer=tokenizer,\n","    mlm=False  # Not masked LM, it's causal\n",")\n","\n","\n","# Boom. Here's the Trainer.\n","trainer = Trainer(\n","    model=model,\n","    args=training_args,\n","    train_dataset=small_tokenized_dataset[\"train\"],\n","    eval_dataset=small_tokenized_dataset[\"val\"],\n","    data_collator=data_collator,\n","\n",")\n"],"metadata":{"id":"MImEcdptdahk","executionInfo":{"status":"ok","timestamp":1750576632150,"user_tz":-330,"elapsed":37,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":50,"outputs":[]},{"cell_type":"code","source":["model.gradient_checkpointing_enable()\n"],"metadata":{"id":"d2PV7qBqd9Yh","executionInfo":{"status":"ok","timestamp":1750576637169,"user_tz":-330,"elapsed":37,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":51,"outputs":[]},{"cell_type":"code","source":["import os\n","os.environ[\"PYTORCH_CUDA_ALLOC_CONF\"] = \"expandable_segments:True\"\n"],"metadata":{"id":"kxUg60KjgRTG","executionInfo":{"status":"ok","timestamp":1750576782683,"user_tz":-330,"elapsed":73,"user":{"displayName":"al nove","userId":"12028300340288841300"}}},"execution_count":53,"outputs":[]},{"cell_type":"code","source":["trainer.train()\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":486},"id":"KdMmhdLudj7E","executionInfo":{"status":"ok","timestamp":1750581080406,"user_tz":-330,"elapsed":1503092,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"1abb501c-5492-4db6-9769-04bc6c1c050a"},"execution_count":54,"outputs":[{"data":{"text/html":["\n","    <div>\n","      \n","      <progress value='1947' max='3000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [1947/3000 46:09 < 24:59, 0.70 it/s, Epoch 1.95/3]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Step</th>\n","      <th>Training Loss</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>500</td>\n","      <td>1.700700</td>\n","    </tr>\n","    <tr>\n","      <td>1000</td>\n","      <td>1.305100</td>\n","    </tr>\n","    <tr>\n","      <td>1500</td>\n","      <td>1.234500</td>\n","    </tr>\n","  </tbody>\n","</table><p>"],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='3000' max='3000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [3000/3000 1:11:12, Epoch 3/3]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Step</th>\n","      <th>Training Loss</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>500</td>\n","      <td>1.700700</td>\n","    </tr>\n","    <tr>\n","      <td>1000</td>\n","      <td>1.305100</td>\n","    </tr>\n","    <tr>\n","      <td>1500</td>\n","      <td>1.234500</td>\n","    </tr>\n","    <tr>\n","      <td>2000</td>\n","      <td>1.229400</td>\n","    </tr>\n","    <tr>\n","      <td>2500</td>\n","      <td>1.185200</td>\n","    </tr>\n","    <tr>\n","      <td>3000</td>\n","      <td>1.203400</td>\n","    </tr>\n","  </tbody>\n","</table><p>"]},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["TrainOutput(global_step=3000, training_loss=1.3097034505208334, metrics={'train_runtime': 4274.3363, 'train_samples_per_second': 0.702, 'train_steps_per_second': 0.702, 'total_flos': 5.3114566606848e+16, 'train_loss': 1.3097034505208334, 'epoch': 3.0})"]},"metadata":{},"execution_count":54}]},{"cell_type":"code","source":["trainer.save_model(\"codex-finetune-final\")\n","tokenizer.save_pretrained(\"codex-finetune-final\")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"b4fUezv2uyxn","executionInfo":{"status":"ok","timestamp":1750581102402,"user_tz":-330,"elapsed":296,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"e0bb7043-4f85-4f19-8e24-a1e02d1e1d34"},"execution_count":55,"outputs":[{"output_type":"execute_result","data":{"text/plain":["('codex-finetune-final/tokenizer_config.json',\n"," 'codex-finetune-final/special_tokens_map.json',\n"," 'codex-finetune-final/vocab.json',\n"," 'codex-finetune-final/merges.txt',\n"," 'codex-finetune-final/added_tokens.json',\n"," 'codex-finetune-final/tokenizer.json')"]},"metadata":{},"execution_count":55}]},{"cell_type":"code","source":["trainer.push_to_hub(\"khushimalik53/coding_copilot\")\n","tokenizer.push_to_hub(\"khushimalik53/coding_copilot\")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":243,"referenced_widgets":["6b3b310c31fb40b4ab5e2a53a0adb2f4","117653515b884a1682857c1d947d8744","b0c5599906a740968f42051e18b21925","5a321919709a452abbf566b7aa5a484e","8c6b75a551994b43a75d620d2a5988d6","60cc9464d0044469b5d81c69226bb3bf","8098fd00de504996971606155be8a884","6e798ae3aca446109f118de8646edbc9","56c33e40415b4d05b1c7a10bec07aa88","4d0d568f3c9f4fa9b678f58f95bb373d","495f85eff9bb41998d90e33ec40b6660","fffbfc9ed8fd43399cc920faf8231de4","63c97080030545a49de90ea4575415b3","f01e15ec1fa14e0781045432656189fa","2122d0244f194c47a8bcea20b962a2eb","0e662e0cdcd44b5092e4dbe5787566f3","2f6ff16a99be45069e4c3c74d1d56738","46eaef18a6f1481996df4a8cb630b117","2a3363f76bd24e28bd1e44ca4da2492d","ba48efe3c4474e898a1504cd2a34e2c2","ecb6f2eaf57945b284d532cf623e6b95","3502612c862040d980808f2aaac5a5d3"]},"id":"h2hpBWdvxFJB","executionInfo":{"status":"ok","timestamp":1750581172393,"user_tz":-330,"elapsed":8515,"user":{"displayName":"al nove","userId":"12028300340288841300"}},"outputId":"d11f63e4-52eb-464c-8413-5cb3c2bf54b1"},"execution_count":57,"outputs":[{"output_type":"display_data","data":{"text/plain":["Uploading...:   0%|          | 0.00/9.12M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6b3b310c31fb40b4ab5e2a53a0adb2f4"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["No files have been modified since last commit. Skipping to prevent empty commit.\n","WARNING:huggingface_hub.hf_api:No files have been modified since last commit. Skipping to prevent empty commit.\n"]},{"output_type":"display_data","data":{"text/plain":["README.md:   0%|          | 0.00/28.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"fffbfc9ed8fd43399cc920faf8231de4"}},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["CommitInfo(commit_url='https://huggingface.co/khushimalik53/coding_copilot/commit/f5978c6f8c8790e76ce1fdcaa843f83c51f1bb83', commit_message='Upload tokenizer', commit_description='', oid='f5978c6f8c8790e76ce1fdcaa843f83c51f1bb83', pr_url=None, repo_url=RepoUrl('https://huggingface.co/khushimalik53/coding_copilot', endpoint='https://huggingface.co', repo_type='model', repo_id='khushimalik53/coding_copilot'), pr_revision=None, pr_num=None)"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":57}]},{"cell_type":"code","source":["metrics = trainer.evaluate(eval_dataset=formatted_dataset[\"test\"])\n","print(metrics)"],"metadata":{"id":"Q9wjkdIax8X1"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["input_text = \"### Instruction:\\nExplain what this function does:\\ndef add(x, y):\\n    return x + y\\n\\n### Response:\\n\"\n","inputs = tokenizer(input_text, return_tensors=\"pt\").to(model.device)\n","outputs = model.generate(**inputs, max_new_tokens=100)\n","print(tokenizer.decode(outputs[0], skip_special_tokens=True))\n"],"metadata":{"id":"D6P3S8sXvbqW"},"execution_count":null,"outputs":[]}]}