From 194ee0e48bcd2f0ec8f212acb66e0cb16397fd12 Mon Sep 17 00:00:00 2001 From: ahwar <20405797+Ahwar@users.noreply.github.com> Date: Sun, 11 Dec 2022 13:00:15 +0500 Subject: [PATCH] docs: improved README.md added more clear steps in README, removed extra cells in jupyter notebook fixed one image was not showing on GitHub simple description of project described the process of running the project more clearly removed extra cells from jupyter notebook --- README.md | 39 +++++++---- convert Huggingface model to ONNX.ipynb | 83 +++++++----------------- images/model-location.png | Bin 0 -> 31676 bytes 3 files changed, 47 insertions(+), 75 deletions(-) create mode 100644 images/model-location.png diff --git a/README.md b/README.md index 3b219a1..5e3a545 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,47 @@ -# Run HuggingFace NER (NLP) Model as Java using ONNX +# Run HuggingFace NER (NLP) Model on Java using ONNX Runtime and DJL +A NLP (Natural Language Processing) Java Application which detects `Names`, `organizaions`, and `locations` in a text by running Hugging face's [Roberta NER model](https://huggingface.co/xlm-roberta-large-finetuned-conll03-english) using [ONNX runtime](https://onnxruntime.ai/docs/get-started/with-java.html) and [Deep Java Library](https://djl.ai/) -## Download files + + +## Installation: +Open Project folder in Java IDE (`Recommended: IntelliJ IDEA Community`) with gradle support and Build the project + + +### Requirements: +1. Java Development Kit JDK version: 11 +2. Gradle version 7+ + +### Download files These files are required to run the project 1. ONNX model 2. `tokenizer.json` file -**Convert the model** +### Convert the ONNX model -To convert HuggingFace NER model to ONNX Open this [Google Colaboratory Notebook](https://colab.research.google.com/drive/1kZx9XOnExVfPoAGHhHRUrdQnioiLloBW#revisionId=0BwKss6yztf4KS0NKaWRiQjc0RGRvQkd6ZFp3OUFhR1lTclBNPQ) run the code as below shown image and follow all the steps +To convert HuggingFace NER model to ONNX Open this [Google Colaboratory Notebook](https://colab.research.google.com/drive/1kZx9XOnExVfPoAGHhHRUrdQnioiLloBW#revisionId=0BwKss6yztf4KS0NKaWRiQjc0RGRvQkd6ZFp3OUFhR1lTclBNPQ) run the code as image shown below and follow all the steps -![run colab code cell](images\run-colab.jpeg) +![run colab code cell](images/run-colab.jpeg) -(the code for above purpose is also saved in jupyter notebook in the file `convert Huggingface model to ONNX.ipynb`. you can run the code using [Jupyter notebook](https://jupyter.org/install)) +(the code for above purpose is also saved in jupyter notebook in the file `convert Huggingface model to ONNX.ipynb`. you can run the code using [Jupyter notebook](https://jupyter.org/install)) -Tokenzer file `tokenizer.json` was taken from this [huggingface repo](https://huggingface.co/xlm-roberta-large-finetuned-conll03-english) -Download the `tokenizer.json` from the [link](https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/raw/main/tokenizer.json) and save in `raw-files` directory +after running the one of above codes your onnx model will be saved in `onnx/` folder. +### Download tokenizer.json +Tokenzer file `tokenizer.json` was taken from this [huggingface repo](https://huggingface.co/xlm-roberta-large-finetuned-conll03-english) +Download the `tokenizer.json` from the [link](https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/raw/main/tokenizer.json) -## Installation: -Open Project folder in Java IDE (`Recommended: IntelliJ IDE`) with gradle support and Build the project +**move files** +Copy files created from above two stesp into `raw-files` directory as shown in the below image +![raw-files path](images/model-location.png) -### Requirements: -1. Java Development Kit JDK version: 11 -2. Gradle version 7+ -### Building project +## Building project Build the project using This button ![how to build project](images/building-project.jpg) diff --git a/convert Huggingface model to ONNX.ipynb b/convert Huggingface model to ONNX.ipynb index 0dad0f3..e533854 100644 --- a/convert Huggingface model to ONNX.ipynb +++ b/convert Huggingface model to ONNX.ipynb @@ -1,18 +1,4 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - } - }, "cells": [ { "cell_type": "markdown", @@ -20,7 +6,7 @@ "id": "xJckl99IHePQ" }, "source": [ - "## Hugging Face to ONNX\n" + "## Hugging Face Model to ONNX\n" ] }, { @@ -31,7 +17,7 @@ }, "outputs": [], "source": [ - "!pip install -q transformers[onnx] transformers[sentencepiece] torch" + "%pip install -q transformers[onnx] transformers[sentencepiece] torch" ] }, { @@ -46,19 +32,10 @@ }, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ - "Framework not requested. Using torch to export to ONNX.\n", - "Downloading: 100% 852/852 [00:00<00:00, 758kB/s]\n", - "Downloading: 100% 2.24G/2.24G [00:57<00:00, 39.2MB/s]\n", - "Downloading: 100% 5.07M/5.07M [00:00<00:00, 45.9MB/s]\n", - "Downloading: 100% 9.10M/9.10M [00:00<00:00, 59.7MB/s]\n", - "Using framework PyTorch: 1.12.1+cu113\n", - "Overriding 1 configuration item(s)\n", - "\t- use_cache -> False\n", "Validating ONNX model...\n", - "tcmalloc: large alloc 1073741824 bytes == 0xb3b2000 @ 0x7f47b38afb6b 0x7f47b38cf379 0x7f46ce7575fe 0x7f46cea041e4 0x7f46ce81397c 0x7f46ce813daa 0x7f46ce82b8f1 0x7f46ce82dea9 0x7f46ce38cf26 0x7f46ce358820 0x7f46cea382be 0x5d746e 0x5d813c 0x4ff515 0x49caa1 0x55e571 0x5d7cf1 0x49ca7c 0x55e571 0x5d7cf1 0x5d9487 0x586306 0x5d808f 0x560200 0x55e571 0x5d7cf1 0x49ec69 0x5d7c18 0x49ec69 0x55e571 0x55ef23\n", "\t-[✓] ONNX model output names match reference model ({'logits'})\n", "\t- Validating ONNX Model output \"logits\":\n", "\t\t-[✓] (3, 9, 8) matches (3, 9, 8)\n", @@ -72,43 +49,27 @@ " --feature=token-classification \\\n", " --model=xlm-roberta-large-finetuned-conll03-english onnx/" ] + } + ], + "metadata": { + "colab": { + "provenance": [] }, - { - "cell_type": "code", - "source": [ - "!zip -r model.zip onnx" - ], - "metadata": { - "id": "RrFoM3zndFZ0" - }, - "execution_count": null, - "outputs": [] + "kernelspec": { + "display_name": "Python 3.8.0 64-bit", + "language": "python", + "name": "python3" }, - { - "cell_type": "markdown", - "source": [ - "Now download the model file as shown in the below image \n", - "\n", - "
\n", - "\n", - "\n", - "![image.png](data:image/png;base64,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)" - ], - "metadata": { - "id": "q0atoqIldM6m" - } + "language_info": { + "name": "python", + "version": "3.8.0" }, - { - "cell_type": "markdown", - "source": [ - "and after extracting it copy onnx folder in to `raw-files` directory in the Java Project Home directory. \n", - "
\n", - "\n", - 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