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---|---|
1 | \n", "2.643200 | \n", "
2 | \n", "2.659200 | \n", "
3 | \n", "2.166800 | \n", "
4 | \n", "2.542200 | \n", "
5 | \n", "2.642800 | \n", "
6 | \n", "2.443900 | \n", "
7 | \n", "2.403800 | \n", "
8 | \n", "2.877700 | \n", "
9 | \n", "2.303500 | \n", "
10 | \n", "2.370900 | \n", "
11 | \n", "2.245700 | \n", "
12 | \n", "2.220300 | \n", "
13 | \n", "2.379900 | \n", "
14 | \n", "2.281200 | \n", "
15 | \n", "2.292100 | \n", "
16 | \n", "2.117700 | \n", "
17 | \n", "2.441100 | \n", "
18 | \n", "2.200500 | \n", "
19 | \n", "2.546300 | \n", "
20 | \n", "1.912300 | \n", "
21 | \n", "2.071200 | \n", "
22 | \n", "2.267200 | \n", "
23 | \n", "2.255400 | \n", "
24 | \n", "2.215400 | \n", "
25 | \n", "2.306700 | \n", "
26 | \n", "2.488700 | \n", "
27 | \n", "2.504100 | \n", "
28 | \n", "1.859200 | \n", "
29 | \n", "2.226500 | \n", "
30 | \n", "2.003200 | \n", "
31 | \n", "2.204300 | \n", "
32 | \n", "2.278500 | \n", "
33 | \n", "2.149400 | \n", "
34 | \n", "2.044000 | \n", "
35 | \n", "2.346900 | \n", "
36 | \n", "2.367300 | \n", "
37 | \n", "2.147700 | \n", "
38 | \n", "2.434000 | \n", "
39 | \n", "2.292900 | \n", "
40 | \n", "2.304800 | \n", "
41 | \n", "2.654700 | \n", "
42 | \n", "2.646200 | \n", "
43 | \n", "2.648800 | \n", "
44 | \n", "2.697100 | \n", "
45 | \n", "2.898000 | \n", "
46 | \n", "2.679200 | \n", "
47 | \n", "2.880400 | \n", "
48 | \n", "2.894300 | \n", "
49 | \n", "3.261200 | \n", "
50 | \n", "3.523700 | \n", "
" ] }, "metadata": {} }, { "output_type": "execute_result", "data": { "text/plain": [ "TrainOutput(global_step=50, training_loss=2.424842336177826, metrics={'train_runtime': 302.6869, 'train_samples_per_second': 0.661, 'train_steps_per_second': 0.165, 'total_flos': 1665685954928640.0, 'train_loss': 2.424842336177826, 'epoch': 0.25})" ] }, "metadata": {}, "execution_count": 21 } ] }, { "cell_type": "code", "source": [ "import transformers\n", "pipeline = transformers.pipeline(\n", " \"text-generation\",\n", " model=model,\n", " tokenizer=tokenizer,\n", " torch_dtype=torch.bfloat16,\n", " trust_remote_code=True,\n", " device_map=\"auto\",\n", ")\n", "\n", "\n", "prompt = \"What are different type of parsers in Langchain?\"\n", "output = pipeline(prompt, max_length=300)\n", "print(output[0]['generated_text'])" ], "metadata": { "id": "6r1XJZlSA4Zj", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "80fdb3e8-ef20-4dc5-fb3d-872de133639e" }, "execution_count": 28, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "What are different type of parsers in Langchain?\n", " everybody has their own favorite parser, but here are some of the most popular ones:\n", "\n", "1. **Python Parser**: This is the default parser in Langchain. It uses the `ast` module to parse Python code.\n", "2. **PyParsing Parser**: This parser is based on the `pyparsing` library. It is a simple and easy-to-use parser that can parse Python code.\n", "3. **PySon Parser**: This parser is based on the `pyson` library. It is a powerful parser that can parse Python code with a lot of features.\n", "4. **PyPy Parser**: This parser is based on the `pypy` library. It is a simple and easy-to-use parser that can parse Python code.\n", "5. **PySock Parser**: This parser is based on the `pysock` library. It is a simple and easy-to-use parser that can parse Python code.\n", "6. **PySock Parser**: This parser is based on the `pysock` library. It is a simple and easy-to-use parser that can parse Python code.\n", "7. **PySock Parser**: This parser is based on the `pysock` library. It is a simple and easy-to-use parser\n" ] } ] }, { "cell_type": "code", "source": [ "!pip install --upgrade huggingface_hub" ], "metadata": { "id": "QNeRdEM-C5qY", "colab": { "base_uri": "https://localhost:8080/", "height": 481 }, "outputId": "ce74df6b-cf64-48ad-e6fa-6b314e75c4d9" }, "execution_count": 29, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/dist-packages (0.17.3)\n", "Collecting huggingface_hub\n", " Using cached huggingface_hub-0.18.0-py3-none-any.whl (301 kB)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (3.12.4)\n", "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2023.6.0)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2.31.0)\n", "Requirement already satisfied: tqdm>=4.42.1 in 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requests->huggingface_hub) (2023.7.22)\n", "Installing collected packages: huggingface_hub\n", " Attempting uninstall: huggingface_hub\n", " Found existing installation: huggingface-hub 0.17.3\n", " Uninstalling huggingface-hub-0.17.3:\n", " Successfully uninstalled huggingface-hub-0.17.3\n", "Successfully installed huggingface_hub-0.18.0\n" ] }, { "output_type": "display_data", "data": { "application/vnd.colab-display-data+json": { "pip_warning": { "packages": [ "huggingface_hub" ] } } }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "!pip install huggingface_hub" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "GhZ4t75o8uBo", "outputId": "d6b3e8c5-97b3-4800-af8a-caddb762ef7e" }, "execution_count": 44, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/dist-packages (0.18.0)\n", "Requirement already satisfied: filelock in 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satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.4)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2.0.7)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2023.7.22)\n" ] } ] }, { "cell_type": "code", "source": [ "import huggingface_hub" ], "metadata": { "id": "nMQnQ43l7DwG" }, "execution_count": 45, "outputs": [] }, { "cell_type": "code", "source": [ "huggingface_hub.login()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 160, "referenced_widgets": [ "41a098019a7b4db1974207885593039e", "12cf6dc906bb48159b8b2c200dec243f", "ce75c0d3c46d4e5e9186e6c00d874499", "e3e0931cddfd45caaca1ba75d4be505b", "f106069c777e4d00843b7195721c8ebc", "15fa8e81bc834f4386b25695e3ed17d3", "eaae171a44664d3480c8b54cc7b865d0", "880e67718aea467585ddcc0ca741fe53", 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"display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='