SamLowe/Roberta Base Go Emotions
Roberta-based model for emotion classification in text
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
UnverifiedOverview
What is SamLowe/Roberta Base Go Emotions?
This model is designed to classify emotions in text using the Roberta architecture, specifically trained on GoEmotions dataset. It's useful for sentiment analysis and understanding emotional nuances in textual data.
Key differentiator
“This Roberta-based model offers high accuracy for emotion classification tasks, specifically trained on the GoEmotions dataset, making it a specialized tool for understanding emotional nuances in text.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
Trained on the GoEmotions dataset, which is primarily in English; performance may degrade for non-English text
Roberta architecture is large and resource-intensive, leading to slower inference times compared to simpler models
Requires specific versions of PyTorch and Transformers library which may cause compatibility issues with other projects
Fit analysis
Who is it for?
✓ Best for
Projects requiring nuanced emotion classification from textual data
Research teams studying sentiment and emotions in text
✕ Not a fit for
Real-time applications where latency is critical due to model size
Applications needing multi-language support beyond English
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with SamLowe/Roberta Base Go Emotions
Step-by-step setup guide with code examples and common gotchas.