GPT-3: Language Models are Few-Shot Learners - GitHub Specifically, we train GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting For all tasks, GPT-3 is applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model
Using OpenAI GPT-4. 1 in Copilot Chat - GitHub Docs GPT-4 1 is one of those models and excels at coding tasks across the entire software development lifecycle, from initial design to bug fixes, maintenance to optimizations For information about the capabilities of GPT-4 1, see the OpenAI documentation GPT-4 1 is currently available in: Copilot Chat in Visual Studio Code
GitHub - openai gpt-2: Code for the paper Language Models are . . . 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