Display benchmark results for models extracting data from PDFs
Evaluate code generation with diverse feedback types
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Merge machine learning models using a YAML configuration file
Display model benchmark results
Display and submit LLM benchmarks
Submit models for evaluation and view leaderboard
Browse and submit model evaluations in LLM benchmarks
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Upload a machine learning model to Hugging Face Hub
LLms Benchmark is a tool designed for model benchmarking, specifically focused on evaluating the performance of models that extract data from PDFs. It provides a comprehensive platform to compare and analyze different models based on their accuracy, efficiency, and reliability in handling PDF data extraction tasks.
• Support for Multiple Models: Evaluate various models designed for PDF data extraction.
• Detailed Performance Metrics: Get insights into accuracy, processing speed, and resource usage.
• Customizable Benchmarks: Define specific test cases to suit your requirements.
• User-Friendly Interface: Easy-to-use dashboard for running and viewing benchmark results.
• Exportable Results: Save and share benchmark outcomes for further analysis or reporting.
What models are supported by LLms Benchmark?
LLms Benchmark supports a variety of models designed for PDF data extraction, including popular open-source and proprietary models. Check the documentation for a full list of supported models.
How long does a typical benchmark take?
The duration of a benchmark depends on the complexity of the PDF files and the number of models being tested. Simple PDFs may take a few seconds, while complex documents with multiple models could take several minutes.
Can I compare results across different runs?
Yes, LLms Benchmark allows you to save and compare results from multiple runs. This feature is particularly useful for tracking improvements in model performance over time.