The process of adjusting model parameters using data and a learning objective.
Neural-network training uses a loss function to evaluate outputs, then backpropagation and optimization to update parameters. It differs from inference with existing weights. Performance on training examples should be evaluated against new data.
Source: Official documentation.
The FID Score is a standard evaluation metric used to measure the quality and realism of generated images.
The tendency of AI models to generate non-real, fabricated, or incorrect information/content. It manifests differently in text, image, and video generation.
The process where a trained AI model makes predictions or generates output on new inputs. In image generation, it corresponds to converting a prompt into an image.
A text command that defines unwanted elements in AI image generation. The model generates images while avoiding the elements specified in the negative prompt.
A text-based instruction or command given to AI models. It is used to describe the desired output and guides the model's generation process.
A discipline that encompasses techniques and strategies for writing prompts to get the best results from AI models. It includes proper word choice, structuring, and parameter usage.