- Added on January 29 2024
- https://chat.openai.com/g/g-47RfCo4zK-perplexity
How to use Perplexity?
-
Step 1 ： Click the open gpts about Perplexity button above, or the link below.
-
Step 2 ： Follow some prompt about Perplexity words that pop up, and then operate.
-
Step 3 ： You can feed some about Perplexity data to better serve your project.
-
Step 4 ： Finally retrieve similar questions and answers based on the provided content.
FAQ from Perplexity?
Perplexity is a metric used in language modeling to measure how well a model can predict a sample of new text. It is an evaluation metric that provides the average log likelihood of all the words in the text based on the model. A lower perplexity score indicates that the model performs better in predicting the text, whereas a higher perplexity score indicates the opposite.
To compute perplexity, the model first calculates the probability of each word in the text sample based on the model's predictions. Then, it takes the inverse logarithm of the average probability of all the words in the sample. The result is the perplexity score, which provides a measure of how surprised the model is by the text sample.
Perplexity is a popular metric in language modeling, but it has some limitations. For instance, it does not consider the context or meaning of the words in the text, and it assumes that each word in the text is independent of the others. Additionally, perplexity does not tell us where the model fails in predicting the text or which words are more difficult for the model to predict, making it a limited evaluation metric.