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| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/Arunprakash-A/164cea8dae89d3c1a2e4e0eb95d5357a/indictrans2_en_indic_1b_.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Install External Dependencies\n", | |
| "* We do not need GPU runtime for this notebook.\n", | |
| "* First, let's install some external dependencies" | |
| ], | |
| "metadata": { | |
| "id": "uvBUdUhna7UU" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "%%capture\n", | |
| "!git clone https://github.com/VarunGumma/IndicTransTokenizer\n", | |
| "!cd IndicTransTokenizer/ && pip install --editable ./" | |
| ], | |
| "metadata": { | |
| "id": "21P5OA0WsFGM" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "* Now restart the session.\n", | |
| "* If you are running this notebook in colab, click \"Runtime\" and click on \"Restart session\".\n" | |
| ], | |
| "metadata": { | |
| "id": "pyom0vRtbb14" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Imports\n", | |
| "* Import the required packages" | |
| ], | |
| "metadata": { | |
| "id": "m0yNwoNfa6HG" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "id": "UexlcYQ3rivc" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import torch\n", | |
| "from transformers import (\n", | |
| " AutoModelForSeq2SeqLM,\n", | |
| " AutoTokenizer,\n", | |
| ")\n", | |
| "from IndicTransTokenizer import IndicProcessor" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "DEVICE = \"cuda\" if torch.cuda.is_available() else \"cpu\"" | |
| ], | |
| "metadata": { | |
| "id": "l3b9oVh2jjUK" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Load The Tokenizer and the Model\n", | |
| "\n", | |
| " * Now we load the tokenizer, the model and learned weights by mentioning \"ai4bharat/indictrans2-en-indic-1B\" as a model_name in `AutoTokenizer` and `AutoModelForSeq2SeqLM` classes\n", | |
| "\n", | |
| " * It will load all the required files and make the model ready for inference.\n" | |
| ], | |
| "metadata": { | |
| "id": "pqmceSEhcRLG" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "model_name = \"ai4bharat/indictrans2-en-indic-1B\"\n", | |
| "tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)\n", | |
| "\n", | |
| "model = AutoModelForSeq2SeqLM.from_pretrained(model_name, trust_remote_code=True)\n", | |
| "\n", | |
| "ip = IndicProcessor(inference=True)" | |
| ], | |
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| }, | |
| "id": "PY3BVWShbShA", | |
| "outputId": "13cbd80b-71b7-4d49-a65b-5cc49874f556" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: 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": { | |
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| { | |
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| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "A new version of the following files was downloaded from https://huggingface.co/ai4bharat/indictrans2-en-indic-1B:\n", | |
| "- tokenization_indictrans.py\n", | |
| ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n" | |
| ] | |
| }, | |
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| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "c94484c9fdcc43cc9ebf32c713a654f6" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "A new version of the following files was downloaded from https://huggingface.co/ai4bharat/indictrans2-en-indic-1B:\n", | |
| "- configuration_indictrans.py\n", | |
| ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "modeling_indictrans.py: 0%| | 0.00/79.6k [00:00<?, ?B/s]" | |
| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "af2715b0df2645b5b8adc4c2b4a4ca62" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "A new version of the following files was downloaded from https://huggingface.co/ai4bharat/indictrans2-en-indic-1B:\n", | |
| "- modeling_indictrans.py\n", | |
| ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "model.safetensors: 0%| | 0.00/4.46G [00:00<?, ?B/s]" | |
| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "d5fd49ce61424b73af5914f3677b2063" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "generation_config.json: 0%| | 0.00/163 [00:00<?, ?B/s]" | |
| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "3ee7040043794e0b9c0b6cf282bcd5cb" | |
| } | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Prepare Inputs" | |
| ], | |
| "metadata": { | |
| "id": "C0XyEHCIhI7k" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "input_sentences = [\n", | |
| " \"When I was young, I used to go to the park every day.\",\n", | |
| " \"We watched a new movie last week, which was very inspiring.\",\n", | |
| " \"If you had met me at that time, we would have gone out to eat.\",\n", | |
| " \"My friend has invited me to his birthday party, and I will give him a gift.\",\n", | |
| "]\n", | |
| "\n", | |
| "src_lang, tgt_lang = \"eng_Latn\", \"hin_Deva\"\n", | |
| "\n", | |
| "batch = ip.preprocess_batch(\n", | |
| " input_sentences,\n", | |
| " src_lang=src_lang,\n", | |
| " tgt_lang=tgt_lang,\n", | |
| ")" | |
| ], | |
| "metadata": { | |
| "id": "3Bs4b7p3dnxQ" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "* Pass it through the tokenizer" | |
| ], | |
| "metadata": { | |
| "id": "kJWK67LNjcRv" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Tokenize the sentences and generate input encodings\n", | |
| "inputs = tokenizer(\n", | |
| " batch,\n", | |
| " truncation=True,\n", | |
| " padding=\"longest\",\n", | |
| " return_tensors=\"pt\",\n", | |
| " return_attention_mask=True,\n", | |
| ").to(DEVICE)" | |
| ], | |
| "metadata": { | |
| "id": "U4cFc2tDjT_P" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Do Inference" | |
| ], | |
| "metadata": { | |
| "id": "B8t9W31Ajwww" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# run the model in inference mode\n", | |
| "with torch.no_grad():\n", | |
| "\n", | |
| " generated_tokens = model.generate(\n", | |
| " **inputs,\n", | |
| " use_cache=True,\n", | |
| " min_length=0,\n", | |
| " max_length=256,\n", | |
| " num_beams=5,\n", | |
| " num_return_sequences=1,\n", | |
| " )" | |
| ], | |
| "metadata": { | |
| "id": "vamruPDJjse9" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Decode the output tokens" | |
| ], | |
| "metadata": { | |
| "id": "YoJTbmpbkJFS" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "with tokenizer.as_target_tokenizer():\n", | |
| " generated_tokens = tokenizer.batch_decode(\n", | |
| " generated_tokens.detach().cpu().tolist(),\n", | |
| " skip_special_tokens=True,\n", | |
| " clean_up_tokenization_spaces=True,\n", | |
| " )" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "9h34541kj9Kk", | |
| "outputId": "6dc5da76-fca2-488c-b5a5-3467c8728934" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:3946: UserWarning: `as_target_tokenizer` is deprecated and will be removed in v5 of Transformers. You can tokenize your labels by using the argument `text_target` of the regular `__call__` method (either in the same call as your input texts if you use the same keyword arguments, or in a separate call.\n", | |
| " warnings.warn(\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Display the translated text" | |
| ], | |
| "metadata": { | |
| "id": "hvxD0qW-kcD8" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Postprocess the translations, including entity replacement\n", | |
| "translations = ip.postprocess_batch(generated_tokens, lang=tgt_lang)\n", | |
| "\n", | |
| "for input_sentence, translation in zip(input_sentences, translations):\n", | |
| " print(f\"{src_lang}: {input_sentence}\")\n", | |
| " print(f\"{tgt_lang}: {translation}\")" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "vd5OURbnkQ7Y", | |
| "outputId": "bd66b15d-6356-4de2-a1b1-48d489188e1f" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "eng_Latn: When I was young, I used to go to the park every day.\n", | |
| "hin_Deva: जब मैं छोटा था, मैं हर दिन पार्क जाता था। \n", | |
| "eng_Latn: We watched a new movie last week, which was very inspiring.\n", | |
| "hin_Deva: हमने पिछले हफ्ते एक नई फिल्म देखी, जो बहुत प्रेरणादायक थी। \n", | |
| "eng_Latn: If you had met me at that time, we would have gone out to eat.\n", | |
| "hin_Deva: अगर आप उस समय मुझसे मिलते तो हम बाहर खाना खाने जाते। \n", | |
| "eng_Latn: My friend has invited me to his birthday party, and I will give him a gift.\n", | |
| "hin_Deva: मेरे दोस्त ने मुझे अपने जन्मदिन की पार्टी में आमंत्रित किया है, और मैं उसे एक उपहार दूंगा। \n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Conclusion\n", | |
| "\n", | |
| " * We have successfully run the model.\n", | |
| " * For more details, visit the github repo:https://github.com/AI4Bharat/IndicTrans2/tree/main/huggingface_interface\n", | |
| " * If the code breaks, feel free to reach us at: mail" | |
| ], | |
| "metadata": { | |
| "id": "x-97zvGQko0m" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [], | |
| "metadata": { | |
| "id": "Dkmu3EmCkmeF" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
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