GPT: Difference between revisions
No edit summary |
No edit summary |
||
| Line 4: | Line 4: | ||
|- | |- | ||
! rowspan="2" | Model | ! rowspan="2" | Model | ||
! Release Date | |||
! rowspan="2" | Parameters | ! rowspan="2" | Parameters | ||
! colspan="3" | Context Window | ! colspan="3" | Context Window | ||
! colspan="5" | Training Data | ! colspan="5" | Training Data | ||
|- | |- | ||
! Tokens | ! Tokens | ||
! Words | ! Words | ||
Revision as of 07:37, 3 March 2023
|
This page needs additional information. |
|---|---|
| Key elements of this article are missing. You can help AI Wiki by expanding it. |
Main GPT Models
| Model | Release Date | Parameters | Context Window | Training Data | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Tokens | Words | Equivalent | Amount | BookCorpus | WebText | CommonCrawl | hello | hello | ||
| GPT-1 | June 11, 2018 | 117 Million | 512 | 358 | ||||||
| GPT-2 | February 14, 2019 | 1.5 Billion | 1024 | 716 | ||||||
| GPT-3 | June 11, 2020 | 175 Billion | 2,048 | 1,433 | ||||||
| GPT-3.5 | January 2022 | 1.3 Bilion, 6 Billion, 175 Billion | 4,000 | 2,800 | ||||||
| ChatGPT | November 30, 2022 | xxx | 4,096 | 2,867 | ||||||
| GPT-4 (v1) |
???? | xxx | 8,000 | 5,600 | ||||||
| GPT-4 (v2) |
???? | xxx | 32,000 | 22,400 | ||||||
What is GPT
GPT, which stands for Generative Pre-trained Transformer, is a type of language model developed by OpenAI. Based on the Transformer architecture and utilizes unsupervised learning, GPT is able to generate text indistinguishable from text written by humans.
How does GPT work?
Using unsupervised learning, GPT is able to generate text by predicting the next word in a sentence based on the context of the words that came before it. The model is trained on a large corpus of text, such as the entire internet, to learn the patterns and relationships between words and how they are used in context.
The Transformer architecture is used in GPT because it is well-suited for processing sequential data, such as text. The Transformer consists of self-attention mechanisms, which allow the model to focus on specific words in a sentence and learn the relationships between them.
Once the model is trained, it can be used for a variety of natural language processing (NLP) tasks, such as text generation, translation, and summarization. The model can also be fine-tuned for specific tasks by training it on smaller, task-specific datasets.
Applications of GPT
GPT has a wide range of applications in the field of NLP. Some of the most notable applications include:
- Text generation: GPT can be used to generate coherent and coherent text that resembles human writing.
- Chatbots: GPT can be used to create conversational agents that can answer questions and hold conversations with users.
- Text classification: GPT can be fine-tuned for text classification tasks, such as sentiment analysis or spam detection.
- Translation: GPT can be used to translate text from one language to another.
Explain Like I'm 5 (ELI5)
GPT is a computer program that can write sentences like a person. It learned how to do this by reading lots of text on the internet. Now it can write new sentences and answer questions by using what it learned. It's like a smart robot that can talk and write in a way that sounds like a person!