Browse and compare AI model evaluations
eRAG-Election: AI กกต. สนับสนุนความรู้การเลือกตั้ง ฯลฯ
Explore and interact with HuggingFace LLM APIs using Swagger UI
Upload a table to predict basalt source lithology, temperature, and pressure
Analyze sentiment of articles about trading assets
Aligns the tokens of two sentences
Ask questions about air quality data with pre-built prompts or your own queries
Find the best matching text for a query
Generate topics from text data with BERTopic
"One-minute creation by AI Coding Autonomous Agent MOUSE"
Analyze text using tuned lens and visualize predictions
List the capabilities of various AI models
Extract... key phrases from text
Skillmix is a platform designed for exploring and comparing AI model evaluations, particularly in the domain of Text Analysis. It provides users with a comprehensive toolset to browse, analyze, and compare various AI models based on their performance metrics, use cases, and capabilities. Whether you're a researcher, developer, or data scientist, Skillmix helps you make informed decisions when selecting AI models for your projects.
• Model Evaluation Browser: Access detailed evaluations of AI models across multiple tasks and datasets.
• Comparison Tools: Compare performance metrics of different models side-by-side.
• Custom Filters: Narrow down models based on specific criteria like accuracy, speed, or supported languages.
• Benchmark Results: View standardized benchmarks to understand model strengths and weaknesses.
• Use Case Recommendations: Get suggestions for the best models suited to your specific task or industry.
What is the primary purpose of Skillmix?
Skillmix is designed to help users explore, evaluate, and compare AI models for text analysis tasks, enabling them to make informed decisions for their projects.
How often are the model evaluations updated?
Skillmix updates its model evaluations regularly to reflect the latest advancements in AI research and technology.
Can I customize the models or training data in Skillmix?
No, Skillmix primarily focuses on evaluating pre-trained models. For custom training or fine-tuning, you may need to integrate the selected model with external tools or frameworks.