View RL Benchmark Reports
Persian Text Embedding Benchmark
Create demo spaces for models on Hugging Face
Text-To-Speech (TTS) Evaluation using objective metrics.
Request model evaluation on COCO val 2017 dataset
Export Hugging Face models to ONNX
Display leaderboard of language model evaluations
Benchmark AI models by comparison
Search for model performance across languages and benchmarks
Evaluate AI-generated results for accuracy
Find and download models from Hugging Face
Calculate GPU requirements for running LLMs
Multilingual Text Embedding Model Pruner
Ilovehf is a tool designed for viewing and analyzing reinforcement learning (RL) benchmark reports. It provides a platform to evaluate and compare the performance of different RL models, helping users gain insights into their effectiveness and efficiency.
• Real-time Tracking: Access live updates on model performance and benchmark results.
• Customizable Filters: Filter reports based on specific models, datasets, or training parameters.
• Performance Metrics: View detailed metrics such as training time, accuracy, and resource usage.
• Visualizations: Interactive charts and graphs to simplify data interpretation.
What is Ilovehf used for?
Ilovehf is used for analyzing and comparing reinforcement learning model performance through detailed benchmark reports.
How do I access Ilovehf?
You can access Ilovehf by visiting its official website or integrating it into your existing workflow.
Can I customize the benchmark reports?
Yes, Ilovehf allows you to customize reports using filters to focus on specific models, datasets, or training parameters.