Sage-Tips

What can GPT-2 be used for?

Due to the broadness of its dataset, and the broadness of its approach, GPT-2 became capable of performing a diverse range of tasks beyond simple text generation: answering questions, summarizing, and even translating between languages in a variety of specific domains, without being instructed in anything beyond how to …

How do you use time series to predict?

When predicting a time series, we typically use previous values of the series to predict a future value. Because we use these previous values, it’s useful to plot the correlation of the y vector (the volume of traffic on bike paths in a given week) with previous y vector values.

What type of model is GPT-2?

unsupervised deep learning transformer-based language model
What Is GPT-2? GPT-2 is an unsupervised deep learning transformer-based language model created by OpenAI back in February 2019 for the single purpose of predicting the next word(s) in a sentence. GPT-2 is an acronym for “Generative Pretrained Transformer 2”.

What is the difference between the model used in GPT-2 model and that of the transformer?

The GPT-2 is built using transformer decoder blocks. BERT, on the other hand, uses transformer encoder blocks. But one key difference between the two is that GPT2, like traditional language models, outputs one token at a time.

How does analysis of time series help in making business forecasting?

Time Series Analysis is used to determine a good model that can be used to forecast business metrics such as stock market price, sales, turnover, and more. By tracking past data, the forecaster hopes to get a better than average view of the future.

How is GPT model trained?

GPT-3, or the third generation Generative Pre-trained Transformer, is a neural network machine learning model trained using internet data to generate any type of text. As a result, GPT-3 is better than any prior model for producing text that is convincing enough to seem like a human could have written it.

What is the GPT-2 model in OpenAI?

GPT-2 is trained to predict next word based on 40GB text. Unlike other model and practise, OpenAI does not publish the full version model but a lightweight version. They mentioned it in their blog: Due to our concerns about malicious applications of the technology, we are not releasing the trained model.

Are GPT-2 models likely to be biased?

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. To avoid having samples mistaken as human-written, we recommend clearly labeling samples as synthetic before wide dissemination.

How to train GPT-2?

GPT-2 use unsupervised learning approach to train the language model. Unlike other model such as ELMo and BERT need 2 stages training which are pre-training and fine-tuning stage. There is no fine-tuning stage for GPT-2. No custom training for GPT-2. OpenAI does not release source code of training GPT-2 (as of Feb 15, 2019).

What is the difference between GPT and GPT-2?

While the difference between GPT and GPT-2 are: To cater different scenario, 4 model with different parameters are trained GPT-2 use unsupervised learning approach to train the language model. Unlike other model such as ELMo and BERT need 2 stages training which are pre-training and fine-tuning stage.