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This behaviour is the source of the following dependency conflicts.\n", "cudf-cu12 25.2.1 requires pyarrow<20.0.0a0,>=14.0.0; platform_machine == \"x86_64\", but you have pyarrow 20.0.0 which is incompatible.\n", "gcsfs 2025.3.2 requires fsspec==2025.3.2, but you have fsspec 2025.3.0 which is incompatible.\n", "pylibcudf-cu12 25.2.1 requires pyarrow<20.0.0a0,>=14.0.0; platform_machine == \"x86_64\", but you have pyarrow 20.0.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0m" ] } ], "source": [ "!pip install -qU sentence_transformers datasets pyarrow" ] }, { "cell_type": "code", "source": [ "from sentence_transformers import SentenceTransformer\n", "\n", "model_id = \"Snowflake/snowflake-arctic-embed-l\"\n", "model = SentenceTransformer(model_id)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 456, "referenced_widgets": [ "1287e1f5ee4747f4b7be32a18c0371ea", "98ed0a843a5540e6b319ea7a5797466d", "8374bfaf4dfc4e5cba24cde4eddb6eb1", 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"ea2860fcd4be47c3869e22d342d90453", "5d580c0e881d44529391bfe013837346", "65644575f25245119fea1fb9c0ce5d8c", "22b1cfbeb9d44a33bb9fb7b914980105", "4001363fd98e413993415b6210fe1a16", "1c00648957814d0899cac456cfddc1cf", "03867c26432045c78f8d6f366eae9652", "ca65f51dafc0480ab0e9956ec0b479de", "8c4d8165964f4faba73684e730a1d9c7", "a510b44cd0a145d298330c7fa0f019f6" ] }, "id": "Qh-l5gQCi2iz", "outputId": "06ba9bf0-c7fa-4af7-847b-554303e3cda6" }, "id": "Qh-l5gQCi2iz", "execution_count": 2, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:86: UserWarning: \n", "Access to the secret `HF_TOKEN` has not been granted on this notebook.\n", "You will not be requested again.\n", "Please restart the session if you want to be prompted again.\n", " warnings.warn(\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "modules.json: 0%| | 0.00/349 [00:00Display W&B run" ], "text/plain": [ "" ] }, "metadata": {}, "execution_count": 10 } ] }, { "cell_type": "code", "source": [ "BATCH_SIZE = 10\n", "EPOCHS = 100\n", "\n", "from datasets import load_dataset\n", "\n", "# Login using e.g. `huggingface-cli login` to access this dataset\n", "ds = load_dataset(\"mafzaal/thedataguy_embed_ft\")\n" ], "metadata": { "id": "X8AQo76tjQOX" }, "id": "X8AQo76tjQOX", "execution_count": 11, "outputs": [] }, { "cell_type": "code", "source": [ "train = ds['train']\n", "\n", "examples = []\n", "for question, context in train:\n", " query = question\n", " text = context\n", " example = InputExample(texts=[query, text])\n", " examples.append(example)" ], "metadata": { "id": "B_7As0KskvX0" }, "id": "B_7As0KskvX0", "execution_count": 24, "outputs": [] }, { "cell_type": "code", "source": [ "\n", "loader = DataLoader(\n", " examples, batch_size=BATCH_SIZE\n", ")" ], "metadata": { "id": "vU0ZZFGQmAHG" }, "id": "vU0ZZFGQmAHG", "execution_count": 26, "outputs": [] }, { "cell_type": "code", "source": [ "from sentence_transformers.losses import MatryoshkaLoss, MultipleNegativesRankingLoss\n", "\n", "matryoshka_dimensions = [768, 512, 256, 128, 64]\n", "inner_train_loss = MultipleNegativesRankingLoss(model)\n", "train_loss = MatryoshkaLoss(\n", " model, inner_train_loss, matryoshka_dims=matryoshka_dimensions\n", ")" ], "metadata": { "id": "vB-rODS7ji9i" }, "id": "vB-rODS7ji9i", "execution_count": 27, "outputs": [] }, { "cell_type": "code", "source": [ "warmup_steps = int(len(loader) * EPOCHS * 0.1)\n", "\n", "model.fit(\n", " train_objectives=[(loader, train_loss)],\n", " epochs=EPOCHS,\n", " warmup_steps=warmup_steps,\n", " output_path='thedataguy_arctic_ft',\n", " show_progress_bar=True,\n", "\n", ")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 301, "referenced_widgets": [ "a7ed0c77b9cc4f32b07d6edaf0592b02", "0829ecf5010c44f785364b7e6e080605", "cd35514a7e6c430ab9478ca553368597", "b0c060f43d5341049b0f236234f5671a", "eab820ab10154587a8ab7b1f06dc32d9", "83e2a41d56d245668778b078b63335a0", "1c09f99f970d424a9ceada5ce223ff65", "a1b77ca163e94fe589c5f6e2296b1494", "c4cb343dd3ba4639977b0c4a1e11a254", "2adfa484ccbf4c77b97ceb4cc09d550f", "2043d498706047bf87cf0c5c35a89481" ] }, "id": "NbvRv4pzjriO", "outputId": "82eeab06-1af3-4edd-f4ec-d126d0ecd87e" }, "id": "NbvRv4pzjriO", "execution_count": 28, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Computing widget examples: 0%| | 0/1 [00:00" ], "text/html": [ "\n", "
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StepTraining Loss
50011.443300
100011.408800
150011.409400
200011.398200
250011.398700
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" ] }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import notebook_login\n", "notebook_login()" ], "metadata": { "id": "ec3m8FxZpmDC", "outputId": "a1dc5e58-486b-48f0-a994-d445f9e2aadc", "colab": { "base_uri": "https://localhost:8080/", "height": 17, "referenced_widgets": [ "fd13548006ae4945ac5466f271485d01", "b21f37896b0443ccb807ac1baa447c42", "44fca9e32f364e5f9dc49adf714b3f55", "9d1650c9e63e4286be9a5646ed0dc11b", "642df745ee7d475db85af5a2b50fbfc6", "3f43ce0be9f145a194f7bc25a4baa30c", "6221df434ba347f6a4f1b583e949d589", "319175349c774c518e4738d10973e3db", "424ee9bddc31425dbf38de4d25560b51", "3c1524991ecd47d7bcf9363a2d69e90a", "4cd8fe0fa9f74a05a4eba8f0597b5226", "38212eb492ef4194b0fe5dba420ebcaa", "c4a9d2a520bf4bb2b02a8dac3c172d0b", "eef784d80c08454799e71185dd5c8c92", "a44929c6198c4d7b959869cd9fc8324b", "469f2c30105946129e0c7943f8d555cc", "32451e32d1494bc3921c61d09ade5985", "39c09a380d5b40a186e996b0b8e0e662", "b63c3935fb1a4309a34a8055f1644baa", "aba64e63a35e49b1b4c39d5204ac9980" ] } }, "id": "ec3m8FxZpmDC", "execution_count": 30, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='


Copy a token from your Hugging Face\ntokens page and paste it below.
Immediately click login after copying\nyour token or it might be stored in plain text in this notebook file.
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