| { |
| "cells": [ |
| { |
| "cell_type": "code", |
| "execution_count": 1, |
| "metadata": { |
| "cellView": "form", |
| "id": "C1rAsD2L-hSO" |
| }, |
| "outputs": [], |
| "source": [ |
| "# @title ###### Licensed to the Apache Software Foundation (ASF), Version 2.0 (the \"License\")\n", |
| "\n", |
| "# Licensed to the Apache Software Foundation (ASF) under one\n", |
| "# or more contributor license agreements. See the NOTICE file\n", |
| "# distributed with this work for additional information\n", |
| "# regarding copyright ownership. The ASF licenses this file\n", |
| "# to you under the Apache License, Version 2.0 (the\n", |
| "# \"License\"); you may not use this file except in compliance\n", |
| "# with the License. You may obtain a copy of the License at\n", |
| "#\n", |
| "# http://www.apache.org/licenses/LICENSE-2.0\n", |
| "#\n", |
| "# Unless required by applicable law or agreed to in writing,\n", |
| "# software distributed under the License is distributed on an\n", |
| "# \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n", |
| "# KIND, either express or implied. See the License for the\n", |
| "# specific language governing permissions and limitations\n", |
| "# under the License" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "id": "b6f8f3af-744e-4eaa-8a30-6d03e8e4d21e" |
| }, |
| "source": [ |
| "# Bring your own ML model to Beam RunInference\n", |
| "\n", |
| "<table align=\"left\">\n", |
| " <td>\n", |
| " <a target=\"_blank\" href=\"https://colab.research.google.com/github/apache/beam/blob/master/examples/notebooks/beam-ml/run_custom_inference.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\" />Run in Google Colab</a>\n", |
| " </td>\n", |
| " <td>\n", |
| " <a target=\"_blank\" href=\"https://github.com/apache/beam/blob/master/examples/notebooks/beam-ml/run_custom_inference.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\" />View source on GitHub</a>\n", |
| " </td>\n", |
| "</table>\n" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "id": "A8xNRyZMW1yK" |
| }, |
| "source": [ |
| "This notebook demonstrates how to run inference on your custom framework using the\n", |
| "[ModelHandler](https://beam.apache.org/releases/pydoc/current/apache_beam.ml.inference.base.html#apache_beam.ml.inference.base.ModelHandler) class.\n", |
| "\n", |
| "Named-entity recognition (NER) is one of the most common tasks for natural language processing (NLP). \n", |
| "NLP locates named entities in unstructured text and classifies the entities using pre-defined labels, such as person name, organization, date, and so on.\n", |
| "\n", |
| "This example illustrates how to use the popular `spaCy` package to load a machine learning (ML) model and perform inference in an Apache Beam pipeline using the RunInference `PTransform`.\n", |
| "For more information about the RunInference API, see [About Beam ML](https://beam.apache.org/documentation/ml/about-ml) in the Apache Beam documentation." |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "id": "299af9bb-b2fc-405c-96e7-ee0a6ae24bdd" |
| }, |
| "source": [ |
| "## Install package dependencies\n", |
| "\n", |
| "The RunInference library is available in Apache Beam versions 2.40 and later.\n", |
| "\n", |
| "For this example, you need to install `spaCy` and `pandas`. A small NER model, `en_core_web_sm`, is also installed, but you can use any valid `spaCy` model." |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 2, |
| "metadata": { |
| "colab": { |
| "base_uri": "https://localhost:8080/" |
| }, |
| "id": "7f841596-f217-46d2-b64e-1952db4de4cb", |
| "outputId": "da04ccb9-0801-47f6-ec9e-e87f0ca4569f" |
| }, |
| "outputs": [], |
| "source": [ |
| "# Uncomment the following lines to install the required packages.\n", |
| "# %pip install spacy pandas\n", |
| "# %pip install \"apache-beam[gcp, dataframe, interactive]\"\n", |
| "# !python -m spacy download en_core_web_sm" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4cc" |
| }, |
| "source": [ |
| "## Learn about `spaCy`\n", |
| "\n", |
| "To learn more about `spaCy`, create a `spaCy` language object in memory using `spaCy`'s trained models.\n", |
| "You can install these models as Python packages.\n", |
| "For more information, see spaCy's [Models and Languages](https://spacy.io/usage/models) documentation." |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 3, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4cd" |
| }, |
| "outputs": [], |
| "source": [ |
| "import spacy\n", |
| "\n", |
| "nlp = spacy.load(\"en_core_web_sm\")\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 4, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4ce" |
| }, |
| "outputs": [], |
| "source": [ |
| "# Add text strings.\n", |
| "text_strings = [\n", |
| " \"The New York Times is an American daily newspaper based in New York City with a worldwide readership.\",\n", |
| " \"It was founded in 1851 by Henry Jarvis Raymond and George Jones, and was initially published by Raymond, Jones & Company.\"\n", |
| "]\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 5, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4cf" |
| }, |
| "outputs": [], |
| "source": [ |
| "# Check which entities spaCy can recognize.\n", |
| "doc = nlp(text_strings[0])\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 6, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4d0" |
| }, |
| "outputs": [ |
| { |
| "name": "stdout", |
| "output_type": "stream", |
| "text": [ |
| "The New York Times 0 18 ORG\n", |
| "American 25 33 NORP\n", |
| "daily 34 39 DATE\n", |
| "New York City 59 72 GPE\n" |
| ] |
| } |
| ], |
| "source": [ |
| "for ent in doc.ents:\n", |
| " print(ent.text, ent.start_char, ent.end_char, ent.label_)\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 7, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4d1" |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "text/html": [ |
| "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n", |
| "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " The New York Times\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n", |
| "</mark>\n", |
| " is an \n", |
| "<mark class=\"entity\" style=\"background: #c887fb; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " American\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">NORP</span>\n", |
| "</mark>\n", |
| " \n", |
| "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " daily\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n", |
| "</mark>\n", |
| " newspaper based in \n", |
| "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " New York City\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n", |
| "</mark>\n", |
| " with a worldwide readership.</div></span>" |
| ], |
| "text/plain": [ |
| "<IPython.core.display.HTML object>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| } |
| ], |
| "source": [ |
| "# Visualize the results.\n", |
| "from spacy import displacy\n", |
| "displacy.render(doc, style=\"ent\")\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 8, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e0" |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "text/html": [ |
| "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">It was founded in \n", |
| "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " 1851\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n", |
| "</mark>\n", |
| " by \n", |
| "<mark class=\"entity\" style=\"background: #aa9cfc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " Henry Jarvis\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PERSON</span>\n", |
| "</mark>\n", |
| " \n", |
| "<mark class=\"entity\" style=\"background: #aa9cfc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " Raymond\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PERSON</span>\n", |
| "</mark>\n", |
| " and \n", |
| "<mark class=\"entity\" style=\"background: #aa9cfc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " George Jones\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PERSON</span>\n", |
| "</mark>\n", |
| ", and was initially published by \n", |
| "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n", |
| " Raymond, Jones & Company\n", |
| " <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n", |
| "</mark>\n", |
| ".</div></span>" |
| ], |
| "text/plain": [ |
| "<IPython.core.display.HTML object>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| } |
| ], |
| "source": [ |
| "# Visualize another example.\n", |
| "displacy.render(nlp(text_strings[1]), style=\"ent\")" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e1" |
| }, |
| "source": [ |
| "## Create a model handler\n", |
| "\n", |
| "This section demonstrates how to create your own `ModelHandler` so that you can use `spaCy` for inference." |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 9, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e2" |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "application/javascript": "\n if (typeof window.interactive_beam_jquery == 'undefined') {\n var jqueryScript = document.createElement('script');\n jqueryScript.src = 'https://code.jquery.com/jquery-3.4.1.slim.min.js';\n jqueryScript.type = 'text/javascript';\n jqueryScript.onload = function() {\n var datatableScript = document.createElement('script');\n datatableScript.src = 'https://cdn.datatables.net/1.10.20/js/jquery.dataTables.min.js';\n datatableScript.type = 'text/javascript';\n datatableScript.onload = function() {\n window.interactive_beam_jquery = jQuery.noConflict(true);\n window.interactive_beam_jquery(document).ready(function($){\n \n });\n }\n document.head.appendChild(datatableScript);\n };\n document.head.appendChild(jqueryScript);\n } else {\n window.interactive_beam_jquery(document).ready(function($){\n \n });\n }" |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| }, |
| { |
| "name": "stdout", |
| "output_type": "stream", |
| "text": [ |
| "The New York Times is an American daily newspaper based in New York City with a worldwide readership.\n", |
| "It was founded in 1851 by Henry Jarvis Raymond and George Jones, and was initially published by Raymond, Jones & Company.\n" |
| ] |
| } |
| ], |
| "source": [ |
| "\n", |
| "import apache_beam as beam\n", |
| "from apache_beam.options.pipeline_options import PipelineOptions\n", |
| "\n", |
| "import warnings\n", |
| "warnings.filterwarnings(\"ignore\")\n", |
| "\n", |
| "\n", |
| "pipeline = beam.Pipeline()\n", |
| "\n", |
| "# Print the results for verification.\n", |
| "with pipeline as p:\n", |
| " (p \n", |
| " | \"CreateSentences\" >> beam.Create(text_strings)\n", |
| " | beam.Map(print)\n", |
| " )\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 10, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e3" |
| }, |
| "outputs": [], |
| "source": [ |
| "# Define `SpacyModelHandler` to load the model and perform the inference.\n", |
| "\n", |
| "from apache_beam.ml.inference.base import RunInference\n", |
| "from apache_beam.ml.inference.base import ModelHandler\n", |
| "from apache_beam.ml.inference.base import PredictionResult\n", |
| "from spacy import Language\n", |
| "from typing import Any\n", |
| "from typing import Dict\n", |
| "from typing import Iterable\n", |
| "from typing import Optional\n", |
| "from typing import Sequence\n", |
| "\n", |
| "class SpacyModelHandler(ModelHandler[str,\n", |
| " PredictionResult,\n", |
| " Language]):\n", |
| " def __init__(\n", |
| " self,\n", |
| " model_name: str = \"en_core_web_sm\",\n", |
| " ):\n", |
| " \"\"\" Implementation of the ModelHandler interface for spaCy using text as input.\n", |
| "\n", |
| " Example Usage::\n", |
| "\n", |
| " pcoll | RunInference(SpacyModelHandler())\n", |
| "\n", |
| " Args:\n", |
| " model_name: The spaCy model name. Default is en_core_web_sm.\n", |
| " \"\"\"\n", |
| " self._model_name = model_name\n", |
| " self._env_vars = {}\n", |
| "\n", |
| " def load_model(self) -> Language:\n", |
| " \"\"\"Loads and initializes a model for processing.\"\"\"\n", |
| " return spacy.load(self._model_name)\n", |
| "\n", |
| " def run_inference(\n", |
| " self,\n", |
| " batch: Sequence[str],\n", |
| " model: Language,\n", |
| " inference_args: Optional[Dict[str, Any]] = None\n", |
| " ) -> Iterable[PredictionResult]:\n", |
| " \"\"\"Runs inferences on a batch of text strings.\n", |
| "\n", |
| " Args:\n", |
| " batch: A sequence of examples as text strings. \n", |
| " model: A spaCy language model\n", |
| " inference_args: Any additional arguments for an inference.\n", |
| "\n", |
| " Returns:\n", |
| " An Iterable of type PredictionResult.\n", |
| " \"\"\"\n", |
| " # Loop each text string, and use a tuple to store the inference results.\n", |
| " predictions = []\n", |
| " for one_text in batch:\n", |
| " doc = model(one_text)\n", |
| " predictions.append(\n", |
| " [(ent.text, ent.start_char, ent.end_char, ent.label_) for ent in doc.ents])\n", |
| " return [PredictionResult(x, y) for x, y in zip(batch, predictions)]\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 11, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e4" |
| }, |
| "outputs": [ |
| { |
| "name": "stdout", |
| "output_type": "stream", |
| "text": [ |
| "The New York Times is an American daily newspaper based in New York City with a worldwide readership.\n", |
| "It was founded in 1851 by Henry Jarvis Raymond and George Jones, and was initially published by Raymond, Jones & Company.\n", |
| "PredictionResult(example='The New York Times is an American daily newspaper based in New York City with a worldwide readership.', inference=[('The New York Times', 0, 18, 'ORG'), ('American', 25, 33, 'NORP'), ('daily', 34, 39, 'DATE'), ('New York City', 59, 72, 'GPE')])\n", |
| "PredictionResult(example='It was founded in 1851 by Henry Jarvis Raymond and George Jones, and was initially published by Raymond, Jones & Company.', inference=[('1851', 18, 22, 'DATE'), ('Henry Jarvis', 26, 38, 'PERSON'), ('Raymond', 39, 46, 'PERSON'), ('George Jones', 51, 63, 'PERSON'), ('Raymond, Jones & Company', 96, 120, 'ORG')])\n" |
| ] |
| } |
| ], |
| "source": [ |
| "# Verify that the inference results are correct.\n", |
| "with pipeline as p:\n", |
| " (p \n", |
| " | \"CreateSentences\" >> beam.Create(text_strings)\n", |
| " | \"RunInferenceSpacy\" >> RunInference(SpacyModelHandler(\"en_core_web_sm\"))\n", |
| " | beam.Map(print)\n", |
| " )\n" |
| ] |
| }, |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e5" |
| }, |
| "source": [ |
| "## Use `KeyedModelHandler` to handle keyed data\n", |
| "\n", |
| "If you have keyed data, use `KeyedModelHandler`." |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 12, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e6" |
| }, |
| "outputs": [], |
| "source": [ |
| "# You can use these text strings with keys to distinguish examples.\n", |
| "text_strings_with_keys = [\n", |
| " (\"example_0\", \"The New York Times is an American daily newspaper based in New York City with a worldwide readership.\"),\n", |
| " (\"example_1\", \"It was founded in 1851 by Henry Jarvis Raymond and George Jones, and was initially published by Raymond, Jones & Company.\")\n", |
| "]\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 13, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e7" |
| }, |
| "outputs": [], |
| "source": [ |
| "from apache_beam.runners.interactive.interactive_runner import InteractiveRunner\n", |
| "from apache_beam.ml.inference.base import KeyedModelHandler\n", |
| "from apache_beam.dataframe.convert import to_dataframe\n", |
| "\n", |
| "pipeline = beam.Pipeline(InteractiveRunner())\n", |
| "\n", |
| "keyed_spacy_model_handler = KeyedModelHandler(SpacyModelHandler(\"en_core_web_sm\"))\n", |
| "\n", |
| "# Verify that the inference results are correct.\n", |
| "with pipeline as p:\n", |
| " results = (p \n", |
| " | \"CreateSentences\" >> beam.Create(text_strings_with_keys)\n", |
| " | \"RunInferenceSpacy\" >> RunInference(keyed_spacy_model_handler)\n", |
| " # Generate a schema suitable for conversion to a dataframe using Map to Row objects.\n", |
| " | 'ToRows' >> beam.Map(lambda row: beam.Row(key=row[0], text=row[1][0], predictions=row[1][1]))\n", |
| " )" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 14, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e8" |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "text/html": [ |
| "\n", |
| " <link rel=\"stylesheet\" href=\"https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css\" integrity=\"sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh\" crossorigin=\"anonymous\">\n", |
| " <div id=\"progress_indicator_25aaf10d571c025a28901bea46b94c93\">\n", |
| " <div class=\"spinner-border text-info\" role=\"status\"></div>\n", |
| " <span class=\"text-info\">Processing... collect</span>\n", |
| " </div>\n", |
| " " |
| ], |
| "text/plain": [ |
| "<IPython.core.display.HTML object>" |
| ] |
| }, |
| "metadata": {}, |
| "output_type": "display_data" |
| }, |
| { |
| "data": { |
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| } |
| ], |
| "source": [ |
| "# Convert the results to a pandas dataframe.\n", |
| "import apache_beam.runners.interactive.interactive_beam as ib\n", |
| "\n", |
| "beam_df = to_dataframe(results)\n", |
| "df = ib.collect(beam_df)\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 15, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4e9" |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "text/html": [ |
| "<div>\n", |
| "<style scoped>\n", |
| " .dataframe tbody tr th:only-of-type {\n", |
| " vertical-align: middle;\n", |
| " }\n", |
| "\n", |
| " .dataframe tbody tr th {\n", |
| " vertical-align: top;\n", |
| " }\n", |
| "\n", |
| " .dataframe thead th {\n", |
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| " }\n", |
| "</style>\n", |
| "<table border=\"1\" class=\"dataframe\">\n", |
| " <thead>\n", |
| " <tr style=\"text-align: right;\">\n", |
| " <th></th>\n", |
| " <th>key</th>\n", |
| " <th>text</th>\n", |
| " <th>predictions</th>\n", |
| " </tr>\n", |
| " </thead>\n", |
| " <tbody>\n", |
| " <tr>\n", |
| " <th>0</th>\n", |
| " <td>example_0</td>\n", |
| " <td>The New York Times is an American daily newspa...</td>\n", |
| " <td>[(The New York Times, 0, 18, ORG), (American, ...</td>\n", |
| " </tr>\n", |
| " <tr>\n", |
| " <th>0</th>\n", |
| " <td>example_1</td>\n", |
| " <td>It was founded in 1851 by Henry Jarvis Raymond...</td>\n", |
| " <td>[(1851, 18, 22, DATE), (Henry Jarvis, 26, 38, ...</td>\n", |
| " </tr>\n", |
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| "text/plain": [ |
| " key text \\\n", |
| "0 example_0 The New York Times is an American daily newspa... \n", |
| "0 example_1 It was founded in 1851 by Henry Jarvis Raymond... \n", |
| "\n", |
| " predictions \n", |
| "0 [(The New York Times, 0, 18, ORG), (American, ... \n", |
| "0 [(1851, 18, 22, DATE), (Henry Jarvis, 26, 38, ... " |
| ] |
| }, |
| "execution_count": 15, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "df" |
| ] |
| }, |
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| "execution_count": null, |
| "metadata": { |
| "id": "7f841596-f217-46d2-b64e-1952db4de4f0" |
| }, |
| "outputs": [], |
| "source": [] |
| } |
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| "name": "Beam RunInference", |
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