GitHub - openai/gpt-2: Code for the paper "Language Models are ...
This repository is meant to be a starting point for researchers and engineers to experiment with GPT-2. For basic information, see our model card.
GitHub - graykode/gpt-2-Pytorch: Simple Text-Generator with …
This repository is simple implementation GPT-2 about text-generator in Pytorch with compress code. The original repertoire is openai/gpt-2. Also You can Read Paper about gpt-2, "Language Models are Unsupervised Multitask Learners". To Understand more detail concept, I recommend papers about Transformer Model.
gpt-2/README.md at master · openai/gpt-2 - GitHub
This repository is meant to be a starting point for researchers and engineers to experiment with GPT-2. For basic information, see our model card.
gpt-2/model_card.md at master · openai/gpt-2 - GitHub
1.5 billion parameters: the fourth and largest GPT-2 version. We have also released 124 million, 355 million, and 774 million parameter models. Paper or other resource for more information
GitHub - minimaxir/gpt-2-simple: Python package to easily retrain ...
A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifically the "small" 124M and "medium" 355M hyperparameter versions). Additionally, this package allows easier generation of text, generating to a file for easy curation, allowing for prefixes to force the text to ...
gpt-2-output-dataset/detector/README.md at master · openai
This directory contains the code for working with the GPT-2 output detector model, obtained by fine-tuning a RoBERTa model with the outputs of the 1.5B-parameter GPT-2 model. For motivations and discussions regarding the release of this detector model, please check out our blog post and report.
GitHub - openai/gpt-2-output-dataset: Dataset of GPT-2 outputs …
We're interested in seeing research in detectability of GPT-2 model family generations. We provide some initial analysis of two baselines, as well as code for the better baseline. Overall, we are able to achieve accuracies in the mid-90s for Top-K 40 generations, and mid-70s to high-80s (depending on model size) for random generations.
gpt-2/LICENSE at master · openai/gpt-2 - GitHub
Code for the paper "Language Models are Unsupervised Multitask Learners" - openai/gpt-2
gpt-2/src/sample.py at master · openai/gpt-2 - GitHub
Code for the paper "Language Models are Unsupervised Multitask Learners" - openai/gpt-2
GitHub - karpathy/minGPT: A minimal PyTorch re-implementation …
openai/gpt-2 has the model definition in TensorFlow, but not the training code; openai/image-gpt has some more modern gpt-3 like modification in its code, good reference as well; huggingface/transformers has a language-modeling example. It is full-featured but as a result also somewhat challenging to trace.