Display model performance data in a dashboard
Explore GenAI model efficiency on ML.ENERGY leaderboard
Predict customer churn based on input details
Track, rank and evaluate open LLMs and chatbots
Calculate memory needed to train AI models
Load AI models and prepare your space
Display model benchmark results
Merge Lora adapters with a base model
Upload ML model to Hugging Face Hub
Analyze model errors with interactive pages
Submit models for evaluation and view leaderboard
Browse and submit model evaluations in LLM benchmarks
Push a ML model to Hugging Face Hub
EnFoBench PVGeneration is a benchmarking tool designed for evaluating the performance of photovoltaic (PV) generation models. It provides a comprehensive dashboard to visualize and analyze key metrics, helping users understand model efficiency and accuracy in various scenarios.
• Performance Comparison: Benchmarks multiple models against each other to identify top performers. • Customizable Metrics: Allows users to define and track specific performance indicators. • Data Visualization: Presents results in an intuitive dashboard for easy interpretation. • Scalability: Supports benchmarking across large datasets and diverse conditions. • Integration: Works seamlessly with popular machine learning frameworks. • Automation: Streamlines the benchmarking process with automated workflows.
What models does EnFoBench PVGeneration support?
EnFoBench PVGeneration supports a wide range of PV generation models, including custom and pre-trained models from popular frameworks.
How long does the benchmarking process typically take?
The duration depends on the complexity of the models and the size of the dataset. Simple models may complete in minutes, while complex models could take hours or longer.
Can I benchmark models across different environmental conditions?
Yes, EnFoBench PVGeneration allows users to simulate various environmental conditions to test model robustness under different scenarios.