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install -U transformers"],"metadata":{"id":"TTRuTCYUiyux","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1761298167279,"user_tz":-180,"elapsed":6549,"user":{"displayName":"hg ahcz","userId":"17954928916181846033"}},"outputId":"92f85549-c061-431c-e812-25e003965b36"},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: transformers in /usr/local/lib/python3.12/dist-packages (4.57.1)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.12/dist-packages (from transformers) (3.20.0)\n","Requirement already satisfied: huggingface-hub<1.0,>=0.34.0 in /usr/local/lib/python3.12/dist-packages (from transformers) (0.35.3)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.12/dist-packages (from transformers) (2.0.2)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from transformers) (25.0)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.12/dist-packages (from transformers) (6.0.3)\n","Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.12/dist-packages (from transformers) (2024.11.6)\n","Requirement already satisfied: requests in /usr/local/lib/python3.12/dist-packages (from transformers) (2.32.4)\n","Requirement already satisfied: tokenizers<=0.23.0,>=0.22.0 in /usr/local/lib/python3.12/dist-packages (from transformers) (0.22.1)\n","Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.12/dist-packages (from transformers) (0.6.2)\n","Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.12/dist-packages (from transformers) (4.67.1)\n","Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<1.0,>=0.34.0->transformers) (2025.3.0)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<1.0,>=0.34.0->transformers) (4.15.0)\n","Requirement already satisfied: hf-xet<2.0.0,>=1.1.3 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<1.0,>=0.34.0->transformers) (1.1.10)\n","Requirement already satisfied: charset_normalizer<4,>=2 in /usr/local/lib/python3.12/dist-packages (from requests->transformers) (3.4.4)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.12/dist-packages (from requests->transformers) (3.11)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.12/dist-packages (from requests->transformers) (2.5.0)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.12/dist-packages (from requests->transformers) (2025.10.5)\n"]}]},{"cell_type":"markdown","source":["## Local Inference on GPU\n","Model page: https://huggingface.co/distilbert/distilbert-base-cased\n","\n","⚠️ If the generated code snippets do not work, please open an issue on either the [model repo](https://huggingface.co/distilbert/distilbert-base-cased)\n","\t\t\tand/or on [huggingface.js](https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/model-libraries-snippets.ts) 🙏"],"metadata":{"id":"s_rg5tx5iyuz"}},{"cell_type":"code","source":["# Use a pipeline as a high-level helper\n","from transformers import pipeline\n","\n","pipe = pipeline(\"fill-mask\", model=\"distilbert/distilbert-base-cased\")"],"metadata":{"id":"coALOWKPiyu0","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1761298596964,"user_tz":-180,"elapsed":769,"user":{"displayName":"hg ahcz","userId":"17954928916181846033"}},"outputId":"53c56d1d-bdcd-4db9-f5ae-bc2c3c2c5d07"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stderr","text":["Device set to use cuda:0\n"]}]},{"cell_type":"code","source":["# Load model directly\n","from transformers import AutoTokenizer, AutoModelForMaskedLM\n","\n","tokenizer = AutoTokenizer.from_pretrained(\"distilbert/distilbert-base-cased\")\n","model = AutoModelForMaskedLM.from_pretrained(\"distilbert/distilbert-base-cased\")"],"metadata":{"id":"E9OGK7R_iyu0","executionInfo":{"status":"ok","timestamp":1761298586477,"user_tz":-180,"elapsed":835,"user":{"displayName":"hg ahcz","userId":"17954928916181846033"}}},"execution_count":3,"outputs":[]},{"cell_type":"code","source":["# Test the pipeline\n","result = pipe(\"Hello I'm a [MASK] model.\")\n","for candidate in result:\n"," print(candidate)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9dQQD1MclFI2","executionInfo":{"status":"ok","timestamp":1761298860985,"user_tz":-180,"elapsed":11,"user":{"displayName":"hg ahcz","userId":"17954928916181846033"}},"outputId":"394b1fea-8a88-457a-f3da-3c2397c90b38"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["{'score': 0.1574956327676773, 'token': 4633, 'token_str': 'fashion', 'sequence': \"Hello I ' m a fashion model.\"}\n","{'score': 0.0604233518242836, 'token': 1848, 'token_str': 'professional', 'sequence': \"Hello I ' m a professional model.\"}\n","{'score': 0.025553790852427483, 'token': 1648, 'token_str': 'role', 'sequence': \"Hello I ' m a role model.\"}\n","{'score': 0.019409094005823135, 'token': 10948, 'token_str': 'celebrity', 'sequence': \"Hello I ' m a celebrity model.\"}\n","{'score': 0.01732577569782734, 'token': 2235, 'token_str': 'model', 'sequence': \"Hello I ' m a model model.\"}\n"]}]},{"cell_type":"code","source":["from transformers import DistilBertTokenizer, DistilBertModel\n","from google.colab import userdata\n","\n","# Get the Hugging Face token from Colab secrets\n","hf_token = userdata.get('HF_TOKEN')\n","\n","tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased', token=hf_token)\n","model = DistilBertModel.from_pretrained(\"distilbert-base-uncased\", token=hf_token)\n","text = \"Replace me by any text you'd like.\"\n","encoded_input = tokenizer(text, return_tensors='pt')\n","output = model(**encoded_input)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":177,"referenced_widgets":["bd143946b29c45ac9efc580f36c023a3","1a947050e1ce4d6fbe918afcbe9be56b","edcdff9089864b3bb1bdc5dd9e3cd579","b2563f36125841f0884cee462c591ab7","e2c26eee2d5e41788284c4732163fb8e","d6b9f9cbe1ef4c0fb37e0938d33d31d8","820704256b4944bdba6c8217fc85647c","b5fbed3fa12d453cbaae847b0885f3e9","af3064c4ea344727979056e4924df121","e4ffd9d30db94e52891e31175d12cd08","8dc28b74cb3f428281b5580665ad492e","438a9b4931ea4e9a9ae3184273c2a34c","8dfdd858a5fa4d8fb4b2d6e0f2c48ca7","0410946b9e0e434ab31e8d0e8eef5ef5","1fa38739a1b947e58588b5df3ddfe210","cde1e555a6f04b098f3597f989c059f3","d9f1edd162c2427f874aa26a6058a1f4","896c80b7aebe44dca64c648f463cc4ac","eab81d48ccd94891bb194a3da9bfd27b","c2cb4566fdc645fe9d6c8d4fb19ecab5","7b22cac0c48343b6bad93a0ea7b1d410","6c2334d4748b4d13a159adcc3c5e6cf0","9cca9f8e4730444ab5ad6e511b520d4e","ba7f4410caa045958a9a5919d311699c","47ba4aaf8d6340078e64ff7feefb8e3b","6565a7c94c4346b1863132fd0a579c8a","64527e0f9b8e4dbb9c929e2a3a10762b","1c1e1c8e123e4aa5bf04ffd98f15b692","dc2a23984ad4481eb5d45cb4a8cb652b","60d15ce290824c71bb1d4109f0f461cf","4b893aa90d9b45538ad04f1a34ba76a2","9de30a91a3cd416383ba7857780985d6","6a5638d2d17d4c94b0d859e04df6d3bf","f7de37bb87094a43a6e4f2a45b80cbf0","89567fce023f48f6adbe6945958b5472","d33614f5bf8c4f8f86fbd797637f7f2e","6612bde1aca84ebbbd70865e461b5d9a","55b3a5ddc4374567bf14b21c7a4d53f1","9ba9e097d83a4bd1aef1c266ed9099fb","68aff187a0874fae89b4e156e1c8e745","52cf681344b24b63ba193f8cb9825fee","fa9d88d18a8442b49b2631d34ea2f9bc","659d190df2ba4f2cb7f321b84d388819","b65dfe67642c41d69ccce3ca5c08a0f6","634cfc109cba49c38cb6c5ae4e9e8cd3","55c331d2108d44fe838a2b3904474029","ab443656566c40ccb1a8fe32a092f89b","9e77ba9d00de4afeb0fde862aa82a3b1","629935e63f31495db1265ff2fdd4a6ee","c2c7c70fe66d43bc8ba014458f7ba952","7d8dca18f78e453b925752961e9924ab","21f316244e4c46c4b0fbf4977f69b701","6c72848d6c1d49098199da8e05208ced","2405e8419d844c0cb9eb1e43ea8958f6","9421eea9826a4e9896b45b971bf80167"]},"id":"Rr61J0fbmG2B","executionInfo":{"status":"ok","timestamp":1761298929839,"user_tz":-180,"elapsed":7963,"user":{"displayName":"hg ahcz","userId":"17954928916181846033"}},"outputId":"6002fa4f-3884-45ac-e676-564b54b396f3"},"execution_count":13,"outputs":[{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json: 0%| | 0.00/48.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"bd143946b29c45ac9efc580f36c023a3"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["vocab.txt: 0%| | 0.00/232k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"438a9b4931ea4e9a9ae3184273c2a34c"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["tokenizer.json: 0%| | 0.00/466k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"9cca9f8e4730444ab5ad6e511b520d4e"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["config.json: 0%| | 0.00/483 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f7de37bb87094a43a6e4f2a45b80cbf0"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["model.safetensors: 0%| | 0.00/268M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"634cfc109cba49c38cb6c5ae4e9e8cd3"}},"metadata":{}}]},{"cell_type":"code","source":["# Show the produced word embeddings\n","print(output.last_hidden_state)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9fw6XL8PmOLO","executionInfo":{"status":"ok","timestamp":1761298957016,"user_tz":-180,"elapsed":43,"user":{"displayName":"hg ahcz","userId":"17954928916181846033"}},"outputId":"912335b3-39fc-47fc-d0ae-1e3068e053c9"},"execution_count":14,"outputs":[{"output_type":"stream","name":"stdout","text":["tensor([[[ 4.4115e-04, -2.6241e-01, -1.0192e-01, ..., -6.2764e-02,\n"," 2.7584e-01, 3.7014e-01],\n"," [ 7.2233e-01, 1.6449e-01, 4.0025e-01, ..., 1.9161e-01,\n"," 4.0458e-01, -5.8094e-02],\n"," [ 2.8198e-01, -1.7430e-01, 3.9075e-02, ..., 2.7681e-02,\n"," 1.1886e-01, 9.1439e-01],\n"," ...,\n"," [ 6.8016e-01, 7.9712e-02, 8.3603e-01, ..., -4.8959e-01,\n"," -2.5017e-01, -2.3518e-01],\n"," [ 3.8106e-02, -8.1751e-01, -3.4076e-01, ..., 4.4815e-01,\n"," 9.6726e-02, -2.0311e-01],\n"," [ 3.5750e-01, 1.9968e-01, 1.7437e-01, ..., 1.5028e-01,\n"," -2.3665e-01, 5.4391e-02]]], grad_fn=<NativeLayerNormBackward0>)\n"]}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"33968277","executionInfo":{"status":"ok","timestamp":1761299017955,"user_tz":-180,"elapsed":43,"user":{"displayName":"hg ahcz","userId":"17954928916181846033"}},"outputId":"6352f01f-7800-40f9-c7ba-d6a404296e83"},"source":["# Decode the input IDs to see the tokens\n","tokens = tokenizer.convert_ids_to_tokens(encoded_input['input_ids'][0])\n","print(tokens)"],"execution_count":15,"outputs":[{"output_type":"stream","name":"stdout","text":["['[CLS]', 'replace', 'me', 'by', 'any', 'text', 'you', \"'\", 'd', 'like', '.', '[SEP]']\n"]}]}]} |