Gpt2 simple colab

 

2 !pip show tensorflow import gpt_2_simple as gpt2 from datetime import datetime from google An Ai that can do Your Homework. ipynb - Colab. com/repos/JohnSnowLabs/spark-nlp-workshop/contents/tutorials/Certification_Trainings from gpt_2_simple. In the tutorial, we are going to fine-tune a German GPT-2 from the Huggingface model hub. The memory usage of LoRA GPT-2 is roughly 35% times less than GPT-2. path. These models are 117M, 124M, 345M, 355M, 774M and 1558M. In total, it contains over 1. generate_to_file(file_name)でgpt2. Samples from the model reflect these improvements and contain coherent paragraphs of text. As fine-tune, data we are using the German Recipes Dataset, which consists of 12190 german recipes with metadata crawled from chefkoch. Note: Development on gpt-2-simple has mostly been superceded by aitextgen, which has similar AI text generation capabilities with more efficient training time and resource usage. 1. We will use the new Trainer class and fine-tune our GPT-2 Model with German recipes from chefkoch. ChatGPT-J has less restrictions than ChatGPT. “If it is not restored to you within a minute, who should shut out the proceedings, and then the prisoner must be put back advance, and then must be removed. In this tutorial, we are going to use the transformers library by Huggingface in their newest version (3. Training. 5B parameter version of GPT-2, a transformer-based language model created and released by OpenAI. !python3 -m pip install nanoGPT. This notebook uses the hugginface finefuning scripts and then uses the TensorFlow version of the genreated models. Sep 29, 2020 · Welcome to another gpt2 video,in this video i finetuned gpt-2 simple and made chatbot from itGPT-2 simple is great package to fine tune chatbot. isfile(file_name): —it shouldn't be needed if you use a May 8, 2021 · A score of 1 indicates that every word that was generated is present in the real text. Feb 6, 2020 · checkpoint_dir=checkpoint_dir, run_name=run_name, steps=25, ) This will automatically grab the latest checkpoint from your checkpoint/run-name folder, load its weights, and continue training where it left off. Note: Colab will reset after 12 hours make sure to save your model checkpoints to google drive around 10-11 hours mark or before, then go to runtime Mar 12, 2020 · GPT2, meanwhile, is pretrained to predict the next word using a causal mask, and is more effective for generation tasks, but less effective on downstream tasks where the whole input yields information for the output. " "!cd checkpoint; zip -r . src. Google ColabのGPU 「Google Colab」のGPUには、「T4」と「K80」があります。「T4」は「K80」より若干高速で、多くのメモリを持ち、より大きな「GPT-2モデル Feb 26, 2020 · One of those is ready-to-go docker images with notebooks ( #3051) but as far as I can see GPT-2 doesn't have a special place there. 'Generate to a variable in memory' is not much of a feature since you can just read a file (or read from stdin). In fact, it can be boiled down to only a few steps: Pre-train a language model using a lot of raw textual data; Adapt this pre-trained model to solve a downstream tasks; However, the description is a bit vague. The pre-trained model contains data from 8 million web pages Sep 6, 2020 · But a lot of them are obsolete or outdated. we want to pre-train a BERT, Longformer, BigBird and GPT-2. you will need to restart your runtime (Runtime -> Restart runtime) After this, you should be able to. [ ] Apr 10, 2021 · The diversity of the dataset causes this simple goal to contain naturally occurring demonstrations of many tasks across diverse domains. we’ve pre processed and cleaned the whole text. requires only images and captions), thus can be applied to any data. My final loss was 0. Convert text sequences into numerical representations. models. To play with this yourself, you will need to have data-eng/ saved in your google drive, you can download them from this link. Model Description: GPT-2 XL is the 1. Jan 6, 2021 · First, we’ll start by creating a new colab project. All model checkpoint layers were used when initializing TFGPT2LMHeadModel. 6 tensorflow-gpu == 1. Colab is especially well suited to machine learning, data science, and education. Blog. but we have no gpu, no muscle computer thats why we hope maybe colab pro can make it happen. Hello! This is a beginner’s story or an introduction if you will. "Install helper library for fine-tuning. In this part, we will learn about all the steps required to fine-tune the Llama 2 model with 7 billion parameters on a T4 GPU. The training took around 70 hours with four GPU NVIDIA GTX 1080-Ti with 11GB of DDR5 and with around 3GB of (processed) training data. In the “Hardware accelerator” section, choose “GPU” as the hardware accelerator. Some libraries may need to be reinstalled or upgraded using the --upgrade flag via pip if Python 2. It can generate text for us with it’s huge pretrained models. Other optional-but-helpful parameters for gpt2. x via the code under below. We designed the codes to be comprehensible. Additionally, this package allows easier generation of text, generating to a file for easy curation, allowing for prefixes to force the text to Sep 4, 2019 · Once open, the first cell (run by pressing Shift+Enter in the cell or mousing-over the cell and pressing the “Play” button) of the notebook installs gpt-2-simple and its dependencies, and loads the package. This is proof of concept for developers that want to create apps with graphics in Colab. (Works in Colab free tier) If you want to generate sprites with a model already trained on Pokemon sprites you can download my model here: pokemon-gpt-2-multigen-250000. [ ] #! pip install datasets transformers. Note: gpt2-client is not compatible with TensorFlow 2. " "Training examples in the dataset file should be separated with a blank line. generate()と同じパラメータを使用して、テキストファイルに生成できます。 生成されたファイルをサイドバーからローカルにダウンロードし、それらを使用して生成され Dec 29, 2022 · Basically, we initialize from a GPT2 checkpoint with init_from and train as normal, except shorter and with a small learning rate. load_dataset import load_dataset, Sampler from gpt_2_simple. At the Judge, again a Judgeyer. Uncomment the following cell and run it. Also You can Read Paper about gpt-2, "Language Models are Unsupervised Multitask Learners". In Colab, we can activate version 1. 5 billion parameters, which is almost 10 times the parameters of GPT. We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3. It was trained on Spanish Wikipedia using Transfer Learning and Fine-tuning techniques. In comparison, the BLEU score for the GPT-2 model without any fine-tuning was of 0. Not really any way that could be simpler. Copy of GPT-2. This repo doesn't accommodate that. You can always try to create this yourself or ask specific questions on Stack Overflow. In addition, our model's training time A trio of Google-Colab notebooks (ipynb) for training a GPT-2 (127M) model from scratch (useful for other / non-English languages) using gpt-2-simple training foreign-language non-english gpt-2 gpt2 gpt-2-simple $ python3 gpt2-generate. I want to fine tune GPT-2 so that it generates better texts for my task. zip. Developed by: OpenAI, see associated research paper and GitHub repo for model developers. Transformer-based Language Model - GPT2. txt --model_name '345M' https://github. As in every beginner’s story, there are pains and gains and this is what this Oct 17, 2021 · Project description. X. Description: Use KerasNLP GPT2 model and samplers to do text generation. >>>> Referring to him as only "the witness", Amrozi accused his brother of deliberately distorting his evidence. The GPT language model was initially introduced in 2018 in the paper “Language Models are Unsupervised Multitask Learners” by Alec Radford, Jeffrey Wu, Rewon Child, David Luan, with the goal of developing a system that could learn from previously produced text. . branch. You can choose models from small to Large. The model does it by using attention. The idea is we use the recipe description to fine-tune our GPT-2 to let us write recipes we can cook. Kashgari is a production-level NLP Transfer learning framework built on top of tf. The full GPT-2 model has 1. Setup: 1) Make sure GPU is enabled, go to edit->notebook settings->Hardware Accelerator GPU. download_gpt2() which downloads the requested model type to the Colaboratory VM (the models are hosted on Feb 2, 2021 · Steps. git and put OpenAI-zipped. Sep 25, 2019 · 1. Not Found. The Colab T4 GPU has a limited 16 GB of VRAM. At our welcome notebook, you can find a simple notebook that loads a dataset of illustrations and displays one of them. This notebook runs on Google Colab. finetune: restore_from: Set to fresh to start training from the base GPT-2, or set to latest to restart training from an existing checkpoint. Mr. After May 27, 2023 · And we are done fine-tuning the model! Before we generate text, let's compare the training time and memory usage of the two models. ファインチューニング. We will use a pretrained (DistilGPT2/ gpt2-medium) model from Huggingface model hub. py --dataset gutenberg-poetry-v001. The original repertoire is openai/gpt-2. colab import files 3. We are looking for a complete guide to train theese models via checkpoints and availabe to Feb 7, 2023 · 下面正式开始训练，分别使用Colab和Kaggle提供的GPU。 Colab版. This repository is simple implementation GPT-2 about text-generator in Pytorch with compress code. zip . 5B model or all of them. Codes from A Comprehensive Guide to Build Your Own Language Model in Python. Here is the attention_mask for GPT2: The prediction for "eating", only utilizes previous words: "<BOS> I love". Jul 29, 2020 · %tensorflow_version 1. pip install gpt-2-simple Dec 13, 2021 · これにより、同ディレクトリ内にgpt2_train_data. n\","," \"\\\"\\\"\\\" % model_name\\n\","," \"\\n\","," \"javascript = \\\"\\\"\\\"\\n\","," \" Click on the "Start" button located at the bottom-left corner of the screen. Jul 13, 2021 · we have a dataset for Turkish language with 35GB. It is considered to be both understandable and optimized. Switch between documentation themes. 15. You can find everything we are doing in this colab notebook. If you want to use this code as your playground check out the 'multisample' branch for more useful notebooks. learning_rate: Learning rate for the training. " Dec 7, 2020 · Traceback (most recent call last): File "/test. Here is the code to evaluate BLEU score for the generated lyrics. ! pip install transformers. 💡 In the notebook, we will prepare the covid dataset for fine-tuning, train and evaluate the model, and get the conversation going with test data or interactive chat input from users! Output. GPT-2 was trained on 40GB of high-quality content using the simple task of predicting the next word. When we start tokenize text to train colab collapse. ChatGPT-J is an open source chatbot with a simple user interface! It can run even on a cell phone. To use this, make a folder named "checkpoint" and place the unzipped pokemon-gpt-2-multigen-250000 folder there then follow above instructions from step 8 on. In this colab notebook we set up a simple outline of how you can use Huggingface to fine tune a gpt2 model on finance titles to generate new possible headlines. 使用Colab进行训练可以直接访问Google Drive，不用下载模型到自己的电脑上，但缺点是只能训练几个小时，同时不能中断。 在训练前，我们在Google Drive中新建一个GPT2文件夹，将train. from_pretrained method with the gpt2 model name and the model_config object. We will use a small sample from CNNDailyMail dataset ( download here) to train the model. That being said, you can have a look at #3063 which is currently implementing generation for GPT-2 and others in Tensorflow. 今回は、先程も紹介した記事の通りにファインチューニングしました。 こちらの記事が大変わかりやすいので、割愛させていただきます。 With the latest Google Colab release, users can open notebooks hosted on the Hugging Face Hub! Let’s look at an example. Select “Change runtime type” from the dropdown menu. ipynb shows how one can load a pretrained GPT2 and generate text given some prompt Library Installation Tutorial. We talk about connections t Jan 16, 2021 · Generative Pre-trained Transformer-2 (a successor to GPT) is a state-of-the-art NLP framework from OpenAI. e. You can choose between the small 117M, medium 345M, large 774M model, xl 1. v1. txtが生成されます。 3. Sign Up. Colab Demo. Just released a Colab notebook that combines Craiyon+Stable Diffusion , to get the best of both worlds. 0. Mar 9, 2021 · GPT is a auto-regressive Language model. A trio of Google-Colab notebooks (ipynb) for training a GPT-2 (127M) model from scratch (useful for other / non-English languages) using gpt-2-simple - Norod/TrainGPT2-127M-FromScratch from transformers. X is used. You have the option to use a free GPU on Google Colab or Kaggle. WARNING: Samples are unfiltered and may contain of fensive content. 6M tweets and their sentiment could be either positive or negative. For a local dataset, I simply drop a txt file in the same folder and call it in file_name =. So, the meeting can be scheduled at 4 pm. The code runs on both platforms. Aug 5, 2020 · my content: Amrozi accused his brother, whom he called "the witness", of deliberately distorting his evidence. Then we can pull the GPT-2 project by using git command. For some reason even with installing this, I was still getting tensorflow>2, so in essence I ran these: !pip install gpt-2-simple==0. x !pip install -q gpt-2-simple import gpt_2_simple as gpt2 from datetime import datetime from google. However, to avoid Could not find 16. x. GPT-4. ChatGPT-J runs completely in the Google Colab notebook. If you're opening this Notebook on colab, you will probably need to install 🤗 Transformers and 🤗 Datasets. This project is a PyTorch implementation of OpenAI GPT-2 model. 500. We can then install Tensorflow in our environment by using the command below. The next step is choosing GPT-2 Model. Building a gp Dec 23, 2020 · GPT-2 is a successor of GPT, the original NLP framework by OpenAI. A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI GPT-2 text generation model (specifically the "small", 124M hyperparameter version). For this purpose I GPT2-small-spanish is a state-of-the-art language model for Spanish based on the GPT-2 small model. pip install gpt2-client. Ideally, gpt2-client is well supported for Python >= 3. just run the notebook in google colab, otherwise you can't save and load the model (that i know of). This is a compilation of code by Max Woolf and my code to build the SQUAD dataset and use it with GPT-2. 0). Jul 8, 2022 · ここではマイドライブ > Colab上に諸々のフォルダやファイルを作成することを考えます。 （マイドライブでも構いませんが、GPT2をクローンするなどの関係上、フォルダを汚したくない場合は新しくフォルダを作成することをおすすめします。 The dataset our GPT-2 models were trained on contains many texts with biases and factual inaccuracies, and thus GPT-2 models are likely to be biased and inaccurate as well. We need to install ngpt and setup the Shakespeare dataset. Open Colab New Notebook. to get started. g. GPT-2 is a direct scale-up of GPT, with more than 10X the Make GPT-2 complete your text in Colab. 2. 3. Apr 13, 2021 · Using State-of-the-Art Pretrained Models (BERT, GPT2, XLNET) for summarizing text with their respective implementation. pkl上传到该文件夹中。 Google Colab This notebook illustrate how to use this repository to train a GPT2 for abstractive summarization. Clone the repo, install dependencies, and download the model weights. Once the browser is opened, look for the "Settings" icon located at the top right corner of the screen (it looks like three vertical dots) and click on it. We’re on a journey to advance and democratize artificial intelligence through open source and open science. !PYTHONPATH=src . E. load_gpt2 ( sess, run_name='discord') # The name of your checkpoint YOURNAME How to Fine-Tune Llama 2: A Step-By-Step Guide. All the layers of TFGPT2LMHeadModel were initialized from the model checkpoint at gpt2. 2 !pip show tensorflow !pip install tensorflow==1. # Import required libraries import torch from transformers import GPT2Tokenizer, GPT2LMHeadModel # Load pre-trained model tokenizer (vocabulary) tokenizer Image captioning is a complicated task, where usually a pretrained detection network is used, requires additional supervision in the form of object annotation. Following the. Nov 13, 2019 · Installation. GPT-2 give State-of-the Art results as you might have surmised already (and will soon see when we get into Python). py", line 1, in <module> import gpt_2_simple ModuleNotFoundError: No module named 'gpt_2_simple' Python == 3. ipynb shows a minimal usage of the GPT and Trainer in a notebook format on a simple sorting example generate. Combining Stable Diffusion and CraiyonAI, this notebook can interpret and improve on the images generated using Craiyon to further improve the quality of the output. Our models are often incoherent or Aug 28, 2020 · 「Google Colab」のGPUは最大20の「batch_size」をサポートでき、gpt2. nlp machine-learning text-classification named-entity-recognition seq2seq transfer-learning ner bert sequence-labeling nlp-framework bert-model text-labeling gpt-2 Nov 24, 2022 · The basic methodology explored by the GPT and GPT-2 models is simple. Fine-Tuning GPT-2 on a Custom Dataset. Feb 16, 2019 · Step 2: Download OpenAI 's open-ai-zipped. Installation. 2) Make a copy to your google drive, click on copy to drive in panel. Google. In his video, Kyle explains his research team's simple theory about how people began to assimilate to the Western world. accumulate import AccumulatingOptimizer tf. gitignore or another one). ← GPT-J GPTBigCode →. So grab your coffee, switch to Google Colab, set the runtime type to GPU In this video, I go over a simple implementation of LoRA for fine-tuning BLOOM 3b on the SQuADv2 dataset for extractive question answering!LoRA learns low-ra The nshepperd finetuning is as simple as PYTHONPATH=src . The Judge, whose eyes had gone in the general direction, leaned back in his seat, and stood ready. !pip install gpt-2-simple. txt if it is present on the machine and downloads it if it isn't. Jan 7, 2021 · January 6th, 2021 Question Answering on SQUAD - Colab. Our library provides training and inference for GPT models up to GPT3 sizes on both TPUs and GPUs. GPT-2 was trained over 40GB of data for text prediction/generation. You are now ready to go with openapi-zipped! Step 3: Deploy OpenAI-zipped. getLogger(__name__) def load_tf_weights_in_image_gpt2 (model, config, gpt2_checkpoint_path): """ Load tf checkpoints in a pytorch model """ try: import re import tensorflow as tf Use the OpenAI GPT-2 language model (based on Transformers) to: Generate text sequences based on seed texts. disable_eager_execution() Aug 21, 2019 · Consider the architecture needs to recall / remember the conversation. You can easily share your Colab notebooks with co-workers or friends, allowing them to comment on your notebooks or even Load the GPT-2 model with the updated config by calling the TFGPT2LMHeadModel. Introduction. Colaboratory/blob/master/Train_a_GPT_2_Text_Generating_Model_w_GPU. Use the OpenAI GPT-2 language model (based on Transformers) to: Generate text sequences based on seed texts. keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding. The model is a pretrained model on English language using a causal language modeling (CLM) objective. You can confirm this by checking the epoch number - it doesn't start again from 0. py 2017年、東京と大阪が初めて合併したことをきっかけに日本文化を深く理解するとともに豊かさを体感出来る場を作りたい。2017年の日本は“豊か”な時代になっているのか。 ChatGPT-J. de. GPT2_Transformer_In_Spark_NLP. Click the “Save” button to apply the changes. 685, which is pretty good. 5B parameter Transformer that achieves state of the art results on 7 out of 8 tested language modeling datasets in a zero-shot setting but still underfits WebText. Oct 17, 2022 · Stable Craiyon. Dec 7, 2022 · The colab notebook from """ Datafile is a text file with one sentence per line _DATASETS/data. No information is sent to an external server (except for the external server that's running the Colab Notebook). <!> Improtant: Chck if hardware GPU accelration is enabled in current runtime. To Understand more detail concept, I recommend papers about Transformer Model. Enabling GPU acceleration will Namespace(batch_size=-1, length=-1, nsamples=1, seed=0, temperature=1, text='Once when I was six years old I saw a magnificent picture in a book, called True Stories from Nature, about the primeval forest. Use fancy JS, instead of default ugly colab interface. txt. Jun 12, 2023 · Follow these simple steps to enable GPU acceleration: Click on the “Runtime” menu at the top of the Colab notebook. The training time of GPT-2 on a 16 GB Tesla T4 (Colab) is 7 minutes, and for LoRA, it is 5 minutes, a 30% decrease. We present a new approach that does not requires additional information (i. gpt2. /your_model_name. ', top_k=0, unconditional=False) Once when I was six years old I saw a magnificent picture in a book, called True Stories from Nature, about the primeval forest. How does pre-training work for language models? Apr 22, 2023 · For the record"}, {'generated_text': "Hello, if you've chosen, if you've given, if you know, it's been a privilege to have it be so for this last year"}, {'generated_text': "Hello, you can do that, too!\n\nWhy, you said the answer was simple, and so you did it, and so I'm"}, {'generated_text': "Hello, I've been watching a TV series called G. Also we use some techniques to improve performance. This will need to be ran the first time you are running this notebook. If you're running out of memory try decreasing the model size (they are {'gpt2', 'gpt2-medium', 'gpt2-large', 'gpt2-xl'}) or possibly decreasing the block_size (context length). ipynb in https://api. Before starting, set Runtime Type to GPU on the top menu bar. 1. If you're opening this notebook locally, make sure your environment has an install from the last version of those Oct 26, 2023 · Locate a code cell or create a new one by clicking the + Code button. May 13, 2022 · Photo by Nadi Borodina on Unsplash GPT2. /train. txt tf_gpt2_keras_lora is the name of the fine-tuned model Mar 26, 2020 · Restart runtime and move back into the GPT2 folder %cd gpt-2 Let’s train the model: Now for the moment we have all been waiting for, fine-tuning the model. [ ] 604800. finetune 8 Fine-Tuning GPT2 - attention mask and pad token id errors This notebook allows you to easily run GPT-2 on colab servers. Copy the one-liner below and run it. gpt-2-simple is installed using pip and show up in pip freeze. Colab notebooks allow you to combine executable code and rich text in a single document, along with images, HTML, LaTeX and more. >>> import ngpt. But can't find the module while trying to work with it. Google has released pre-trained BERT models (only saw a 345mb) so you can avoid retraining things. compat. start_tf_sess () gpt2. Collaborate on models, datasets and Spaces. , if you'd previously trained 25 epochs, it'll Jan 29, 2024 · JSONDecodeError: Unexpected UTF-8 BOM (decode using utf-8-sig): line 1 column 1 (char 0) ---While Tuning gpt2. We will train the model on the simplebooks-92 corpus, which is a dataset made from several novels. ipynb Nov 3, 2019 · Using GPT2-simple, Google Colab and Google Run. ”. 7. 288. " "When fine-tuning on a single GPU, only the 124M and 335M size models can be used. demo. To avoid having samples mistaken as human-written, we recommend clearly labeling samples as synthetic before wide dissemination. In this notebook we walk you through TPU training (or finetuning!) and sampling using the freely available colab TPUs. Here, we will use the Twitter Sentiment dataset, that can be download from here. 2. Oct 17, 2021 · The Colab Notebook has also been update to no longer use TensorFlow 1. We obtain an average BLEU score of 0. py --dataset src/corpus/corpus. Welcome to the colab notebook for GPTNeo - a fully open source implementation of GPT like models for mesh-tensorflow by EleutherAI. Feb 5, 2021 · So, we will work with Tensorflow 1. 5 and TensorFlow >= 1. nn as nn import logging logger = logging. Run the Installation Command: In the code cell, type the following command and then run the cell by clicking the Play button Jul 25, 2022 · GPT is a Transformer-based model that allows you to generate sophisticated text from a prompt. If you do not require using TensorFlow, I recommend using aitextgen instead. When you create your own Colab notebooks, they are stored in your Google Drive account. . Below you will find the code to run a basic answer bot using the GPT-2 model you trained with the steps above: import discord, datetime import gpt_2_simple as gpt2 import asyncio, random, string sess = gpt2. Next step is downloading gpt-2 library from pip. Attorney-General then, following his leader's After that, he got cock obsessed, sized his ass ===== SAMPLE 128 ===== a professor of geography and early history at Princeton University. Faster examples with accelerated inference. You can train and train but - you're going to get random responses on each call. One can also use any dataset of their choice. Here is a list of their availability: - Andrew: 11 am to 3 pm - Joanne: noon to 2 pm, and 3:30 pm to 5 pm - Hannah: noon to 12:30 pm, and 4 pm to 6 pm Based on their availability, there is a 30-minute window where all three of them are available, which is from 4 pm to 4:30 pm. modeling_gpt2 import GPT2Model,GPT2LMHeadModel import torch import torch. Install client via pip. sample_every: Number of steps to print example output print_every: Number of steps to print training progress. On Hugging Face, you can preview the notebook, see the history of the file (by looking at the commits First Time Running. I Feb 18, 2020 · Our largest model, GPT-2, is a 1. npz --batch_size 2. You should be able to remove the logic around if not os. It provides model training, sentence generation, and metrics visualization. In this tutorial, you will learn to use KerasNLP to load a pre-trained Large Language Model (LLM) - GPT-2 model (originally invented by OpenAI), finetune it to a specific text style, and generate text based on users' input (also known as prompt). Jan 8, 2021 · Open AI GPT-2 is a transformer-based, autoregressive language model that shows competetive performance on multiple language tasks, especially (long form) text generation. Later in the notebook is gpt2. Jul 11, 2021 · To test the performance of different language models, we will compare the accuracy of the models after finetuning on a simple task — sentiment detection. 4. I made 355M work on Colab Pro but used the gpt-2-simple==0. 06 after 4000 iterations and seems to be able to get contextual references pretty damn Now copy the token for the bot. Look for the Google Chrome icon and click on it to launch the browser. git in your PATH as your repository (if there isn' t one already, you should create a . It is a good dataset for this example since it has a small vocabulary and high word frequency, which is beneficial when training a model with few Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. com/sarthakmalik/GPT2. If I read the example correctly on GitHub, it loads shakespeare. github. fg yp pb xm jv ez vs oi od gj