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sentence_transformers\n", "!pip -q install tiktoken\n", "!pip -q install faiss-cpu\n" ], "metadata": { "id": "dNXSOvA8SQFX", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "050d591d-8dc4-44f0-f515-797e732e93f3" }, "execution_count": 2, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m17.4/17.4 MB\u001b[0m \u001b[31m38.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m28.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.0/57.0 kB\u001b[0m \u001b[31m4.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m288.1/288.1 kB\u001b[0m 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"import os\n", "import requests\n", "import io\n", "import random\n", "import time\n", "from getpass import getpass\n", "from langchain import HuggingFaceHub\n", "from langchain.embeddings import HuggingFaceEmbeddings\n", "from langchain.text_splitter import TokenTextSplitter, CharacterTextSplitter\n", "from langchain import PromptTemplate, LLMChain\n", "from langchain.chains.question_answering import load_qa_chain\n", "from langchain.vectorstores import FAISS\n", "from langchain.document_loaders import TextLoader\n", "from langchain.callbacks.manager import CallbackManager\n", "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n", "from langchain.llms import LlamaCpp" ], "metadata": { "id": "7igk0UkdSLYM", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "26a40670-0dec-4d3b-dc30-c740ef92a913" }, "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "WARNING:langchain.utilities.powerbi:Could not import azure.core python package.\n" ] } ] }, { "cell_type": "markdown", "source": [ "## Wichtige Konstanten" ], "metadata": { "id": "GYD_dW5mxsra" } }, { "cell_type": "code", "source": [ "# Enter your Hugging Face API Token here\n", "os.environ[\"HUGGINGFACEHUB_API_TOKEN\"] = getpass()\n", "REPO_ID = \"declare-lab/flan-alpaca-large\"\n", "#REPO_ID = \"decapoda-research/llama-7b-hf\"\n", "TEXT_URL = \"https://www.gutenberg.org/cache/epub/164/pg164.txt\"\n" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "h1CbYr7PUloM", "outputId": "01f39714-c9dd-4ce2-feeb-9ce3fd9aad04" }, "execution_count": 5, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "··········\n" ] } ] }, { "cell_type": "markdown", "source": [ "## Sprachmodell und Embeddings initialisieren" ], "metadata": { "id": "A0cARc-lyExZ" } }, { "cell_type": "code", "source": [ "llm = HuggingFaceHub(repo_id=REPO_ID, model_kwargs={\"temperature\":0, \"max_length\":512})" ], "metadata": { "id": "nOXT9vV5UfKx" }, "execution_count": 6, "outputs": [] }, { "cell_type": "code", "source": [ "embeddings = HuggingFaceEmbeddings()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 465, "referenced_widgets": [ "ea111d90a17b42b79030b6031bb3eceb", "4007af5c80a046c4b9a9ad07b96798a2", "dfa3ea05b81b4a6083f170655487419b", "7af5b714a981489b8febc96b13c096ab", "969455c8324b4d2d9241580b380bc119", "34c57bb20e7f4ed38901eca09d858750", "21d3cc537c034cca90d7da485cc208fc", "9a761f29beb046888005d27ac5dda676", "72f202b18548443f951a4bcc28be6ca4", "ce82a7b26e954f25b8124e8aff027a08", "1443824d3db54f3e9a0c71568dba2369", "d7ea0aef4e374c13b25b9007ac6dbc2f", "5e21490de93b481790a56ef2ceb5db30", "b7eb7b0d518e4b7086ae132cd300584c", "8b5dd69aecc8488098e3dc089c596418", "b0ca0c5e708d46f8bbca2e40f0ea44a9", "32d881d20eae4932aa9c434e35541c2c", "4fb5576ecea34882a9387673f95ebaf7", "df5f4a475b854ba98fbf87e4812fc1ed", "96d6bdb01b0540ec82c0d542a1160cc2", "df1a7d8fce2e4a17960d125f2b0ce392", 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7, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)a8e1d/.gitattributes: 0%| | 0.00/1.18k [00:00" ], "application/javascript": [ "(async (port, path, width, height, cache, element) => {\n", " if (!google.colab.kernel.accessAllowed && !cache) {\n", " return;\n", " }\n", " element.appendChild(document.createTextNode(''));\n", " const url = await google.colab.kernel.proxyPort(port, {cache});\n", "\n", " const external_link = document.createElement('div');\n", " external_link.innerHTML = `\n", "
\n", " Running on \n", " https://localhost:${port}${path}\n", " \n", "
\n", " `;\n", " element.appendChild(external_link);\n", "\n", " const iframe = document.createElement('iframe');\n", " iframe.src = new URL(path, url).toString();\n", " iframe.height = height;\n", " iframe.allow = \"autoplay; camera; microphone; clipboard-read; clipboard-write;\"\n", " iframe.width = width;\n", " iframe.style.border = 0;\n", " element.appendChild(iframe);\n", " })(7860, \"/\", \"100%\", 500, false, window.element)" ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Keyboard interruption in main thread... closing server.\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [] }, "metadata": {}, "execution_count": 32 } ] } ] }