{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Install Dependencies"
      ],
      "metadata": {
        "id": "39AMoCOa1ckc"
      }
    },
    {
      "metadata": {
        "id": "VoHxuLPu7s37"
      },
      "cell_type": "code",
      "source": [
        "! wget -q https://github.com/protocolbuffers/protobuf/releases/download/v3.19.0/protoc-3.19.0-linux-x86_64.zip\n",
        "! unzip -o protoc-3.19.0-linux-x86_64.zip -d /usr/local/"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Install LiteRT Pipeline"
      ],
      "metadata": {
        "id": "qGAaAKzYK5ei"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install git+https://github.com/google-ai-edge/ai-edge-apis.git#subdirectory=litert_tools"
      ],
      "metadata": {
        "id": "43tAeO0AZ7zp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create Pipeline from model file"
      ],
      "metadata": {
        "id": "K5okZCTgYpUd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from litert_tools.pipeline import pipeline\n",
        "runner = pipeline.load(\"litert-community/Hammer2.1-1.5b\", \"Hammer2.1-1.5b_seq128_q8_ekv1280.task\")"
      ],
      "metadata": {
        "id": "3t47HAG2tvc3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Generate text from model"
      ],
      "metadata": {
        "id": "dASKx_JtYXwe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Disclaimer: Model performance demonstrated with the Python API in this notebook is not representative of performance on a local device.\n",
        "prompt = \"What is the capital of France?\"\n",
        "output = runner.generate(prompt, max_decode_steps=None)"
      ],
      "metadata": {
        "id": "wT9BIiATkjzL"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}