setup_popular_models: Quick Setup for Popular Models

In transforEmotion: Sentiment Analysis for Text, Image and Video using Transformer Models

Quick Setup for Popular Models

Description

Convenience function to quickly add popular vision models with pre-configured settings.

Usage

setup_popular_models(models)

Arguments

models

Character vector of model shortcuts to add. Available options: "blip-base": BLIP base model for image captioning and VQA "blip-large": BLIP large model for better performance "align-base": ALIGN base model for image-text alignment

Value

Invisibly returns TRUE if all models added successfully

Examples

## Not run: 
# Add BLIP models for image captioning
setup_popular_models("blip-base")

# Add multiple experimental models at once
setup_popular_models(c("blip-base", "blip-large", "align-base"))

# Then use them in your analysis
list_vision_models()  # See all available models
result <- image_scores("image.jpg", c("happy", "sad"), model = "blip-base")

## End(Not run)

transforEmotion documentation built on Jan. 8, 2026, 5:06 p.m.