Hugging_face_with_langchain_mine.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "id": "bfdeb163-9899-43b5-adab-e31f71c446a9",
      "metadata": {
        "id": "bfdeb163-9899-43b5-adab-e31f71c446a9"
      },
      "source": [
        "# Step 1 : Install libraries."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "id": "2ba9566e-5dec-4d6e-97ea-728411e54a7e",
      "metadata": {
        "id": "2ba9566e-5dec-4d6e-97ea-728411e54a7e"
      },
      "outputs": [],
      "source": [
        "# ! pip install huggingface_hub\n",
        "# ! pip install transformers\n",
        "# ! pip install accelerate\n",
        "# ! pip install bitsandbytes"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ! pip install langchain"
      ],
      "metadata": {
        "id": "4CGRiLkVM-dj"
      },
      "id": "4CGRiLkVM-dj",
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "id": "88a56b3d-74f6-4476-ab84-8867ccfd5e6f",
      "metadata": {
        "id": "88a56b3d-74f6-4476-ab84-8867ccfd5e6f"
      },
      "source": [
        "# Step 2: Import the libraries which are required"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "id": "a0b0f31c-d789-4f7b-8973-af4f9fc9a0f6",
      "metadata": {
        "id": "a0b0f31c-d789-4f7b-8973-af4f9fc9a0f6"
      },
      "outputs": [],
      "source": [
        "from langchain import PromptTemplate ,HuggingFaceHub,LLMChain"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "15d6b9a8-b3e3-430b-9fd2-71c7871d3881",
      "metadata": {
        "id": "15d6b9a8-b3e3-430b-9fd2-71c7871d3881"
      },
      "source": [
        "# Step 3 : Setting the enviorment"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "a82c3b51-fb74-4775-a995-50c4f3d29cf9",
      "metadata": {
        "id": "a82c3b51-fb74-4775-a995-50c4f3d29cf9"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "os.environ['HUGGINGFACEHUB_API_TOKEN']=\"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\""
      ]
    },
    {
      "cell_type": "markdown",
      "id": "beaa278e-335f-4b59-bf95-3813a8e15d05",
      "metadata": {
        "id": "beaa278e-335f-4b59-bf95-3813a8e15d05"
      },
      "source": [
        "### Text2Text Generation Models | Seq2Seq Models | Encoder-Decoder Models"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "id": "ef313e90-f7ad-496a-83ae-cc879fb504d3",
      "metadata": {
        "id": "ef313e90-f7ad-496a-83ae-cc879fb504d3"
      },
      "outputs": [],
      "source": [
        "prompt = PromptTemplate(\n",
        "    input_variables=[\"product\"],\n",
        "    template=\"What is a good name for a company that makes {product}\"\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "id": "a91f1666-b838-4fd8-bdfc-716a459ea24f",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a91f1666-b838-4fd8-bdfc-716a459ea24f",
        "outputId": "8b58ff0e-ad2b-4da2-feea-beedd1af2334"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/langchain_core/_api/deprecation.py:119: LangChainDeprecationWarning: The class `HuggingFaceHub` was deprecated in LangChain 0.0.21 and will be removed in 0.2.0. Use HuggingFaceEndpoint instead.\n",
            "  warn_deprecated(\n"
          ]
        }
      ],
      "source": [
        "chain = LLMChain(llm=HuggingFaceHub(repo_id='google/flan-t5-large', model_kwargs={'temperature':0}),prompt = prompt)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "id": "8761a3ba-1d61-4b29-861c-c6491fe5e893",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "8761a3ba-1d61-4b29-861c-c6491fe5e893",
        "outputId": "b00cd684-d6d9-4f0d-fcf5-18050ce87789"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'nikon'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "chain.run(\"camera\").strip()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "id": "e7beba5f-4780-4c7b-9a1f-320da9017c8d",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "e7beba5f-4780-4c7b-9a1f-320da9017c8d",
        "outputId": "ea9cb222-d3c7-4781-9cb0-239aad3b50e2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'imax'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "chain.run(\"image\").strip()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "id": "538c479b-56c8-4381-8f2b-9b6e5a0e692b",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "538c479b-56c8-4381-8f2b-9b6e5a0e692b",
        "outputId": "85df14ab-5680-4940-e512-4b3dc99f856d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'mcdonalds'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "chain.run(\"mixer\").strip()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "id": "d9ae28b2-969a-46c7-92bd-a5d3e80a6539",
      "metadata": {
        "id": "d9ae28b2-969a-46c7-92bd-a5d3e80a6539"
      },
      "outputs": [],
      "source": [
        "chain2 = LLMChain(llm=HuggingFaceHub(repo_id='facebook/mbart-large-50', model_kwargs={'temperature':0.5}),prompt = prompt)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "id": "4392a74d-5f8b-4dfa-9fa0-cb4f24be7309",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "4392a74d-5f8b-4dfa-9fa0-cb4f24be7309",
        "outputId": "49e73eed-d71f-4346-9840-27fceceaae58"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'What is a good name for a company that makes bike'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "chain2.run(\"bike\")"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "07321722-7a8d-4b69-9159-6f394416c5cb",
      "metadata": {
        "id": "07321722-7a8d-4b69-9159-6f394416c5cb"
      },
      "source": [
        "# Text Generation Models | Decoder Only Models"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "id": "75775808-144b-48fc-83c9-c1cf3363285e",
      "metadata": {
        "id": "75775808-144b-48fc-83c9-c1cf3363285e"
      },
      "outputs": [],
      "source": [
        "from langchain.llms import HuggingFacePipeline\n",
        "import torch\n",
        "from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline, AutoModelForSeq2SeqLM\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "id": "44fe1fa2-a0c9-4e86-8df5-8a01c7b73932",
      "metadata": {
        "id": "44fe1fa2-a0c9-4e86-8df5-8a01c7b73932"
      },
      "outputs": [],
      "source": [
        "model_id='google/flan-t5-large'"
      ]
    },
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        "outputId": "a520921b-ead0-4ed2-ae42-8f017f5d93f2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/2.54k [00:00<?, ?B/s]"
            ],
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          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/2.42M [00:00<?, ?B/s]"
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        {
          "output_type": "display_data",
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              "special_tokens_map.json:   0%|          | 0.00/2.20k [00:00<?, ?B/s]"
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          "metadata": {}
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      ],
      "source": [
        "tokenizer=AutoTokenizer.from_pretrained(model_id)"
      ]
    },
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/662 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "22ba765a436746c1978094873533ae77"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/3.13G [00:00<?, ?B/s]"
            ],
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "a9c6f569a36a4678a35bf23ca0fab5f3"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "generation_config.json:   0%|          | 0.00/147 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "073a6c9041994dcb92f4b7380766e4d8"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "model = AutoModelForSeq2SeqLM.from_pretrained(model_id,device_map='auto')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "id": "306ca00f-26c6-4a5e-b04e-6813c857f0c1",
      "metadata": {
        "id": "306ca00f-26c6-4a5e-b04e-6813c857f0c1"
      },
      "outputs": [],
      "source": [
        "pipeline = pipeline(\"text2text-generation\", model=model, tokenizer=tokenizer, max_length=128)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "id": "f232b423-85ce-4401-9a69-a48d9ce8fc70",
      "metadata": {
        "id": "f232b423-85ce-4401-9a69-a48d9ce8fc70"
      },
      "outputs": [],
      "source": [
        "local_llm = HuggingFacePipeline(pipeline=pipeline)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "id": "5890f067-c917-48a1-a5ee-7d366195b3f9",
      "metadata": {
        "id": "5890f067-c917-48a1-a5ee-7d366195b3f9"
      },
      "outputs": [],
      "source": [
        "prompt = PromptTemplate(\n",
        "    input_variables=[\"name\"],\n",
        "    template=\"Can you tell me about footballer {name}\"\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "id": "f9bee7c3-f1c7-43cb-9cce-a2a9e7c3870f",
      "metadata": {
        "id": "f9bee7c3-f1c7-43cb-9cce-a2a9e7c3870f"
      },
      "outputs": [],
      "source": [
        "chain = LLMChain(llm=local_llm,prompt = prompt)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "id": "923ab857-aad7-4e74-9bdc-8d73e6439ec3",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "923ab857-aad7-4e74-9bdc-8d73e6439ec3",
        "outputId": "90ff264b-0e1e-4712-9a0f-25fc14422c62"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Sunil Chetri (born 24 August 1971) is a former Indian footballer who played as a forward.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ],
      "source": [
        "chain.run(\"sunil chetri\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
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