eval
Twinkle Eval：高效且準確的 AI 評測工具
Explore the Twinkle Eval default config template structure and learn how to customize it. Understand LLM settings, model parameters, and evaluation workflows with ease. Get started today!
How to Configure Google Drive Integration for Automatic Result Backup in Twinkle EvalEasily configure Google Drive integration for Twinkle Eval. Automatically back up logs and results to a timestamped Google Drive folder after each evaluation.
How the HuggingFace Dataset Download Feature Works in Twinkle EvalDiscover how Twinkle Eval's HuggingFace dataset download feature uses the twinkle_eval.dataset module to fetch public datasets, discover configurations, and save subsets locally as Parquet files for offline evaluation.
Difference Between `results_{timestamp}.json` and `eval_results_{timestamp}.jsonl` in twinkle-evalUnderstand the difference between results_{timestamp}.json and eval_results_{timestamp}.jsonl in twinkle-eval. Get high-level summaries or granular per-question logs for analysis.
How to Debug Evaluation Failures Using the Logging Configuration in Twinkle EvalDebug Twinkle Eval evaluation failures by inspecting timestamped log files in the logs directory. Utilize log_info, log_error, and log_warning helpers for detailed diagnostics.
How EvaluationStrategyFactory Registers and Manages Evaluation Strategies in ai-twinkle/evalDiscover how the EvaluationStrategyFactory in ai-twinkle/eval registers and manages evaluation strategies. Learn about dynamic registration and decoupling strategy instantiation.
How to Use Twinkle Eval Programmatically with the Python API: A Complete GuideLearn to use Twinkle Eval programmatically with Python. This guide shows you how to import TwinkleEvalRunner, initialize, and run evaluations for your datasets.
How Twinkle Eval Handles SSL Verification and API Timeout ConfigurationLearn how Twinkle Eval manages SSL verification and API timeout settings. Explore secure defaults and streamlined configuration within config.yaml for enhanced API interactions.
JSON vs CSV Export Formats in Twinkle Eval: Key Differences and Use CasesCompare JSON vs CSV export formats in Twinkle Eval. Understand key differences: JSON for nested data, CSV for tabular analysis. Choose the best format for your evaluation results.
How to Configure System Prompts for Different Languages in Twinkle EvalEasily configure system prompts for multiple languages in Twinkle Eval. Define language-specific prompts and map dataset paths for seamless multilingual evaluation.
How to Add Support for a New Dataset Format in Twinkle Eval: A Complete GuideEasily add support for new dataset formats in ai-twinkle/eval. Learn the simple three-step process to extend Twinkle Eval's capabilities with our complete guide.
How Twinkle Eval Implements Multi-Run Stability Analysis for LLM EvaluationDiscover how Twinkle Eval performs multi-run stability analysis by repeating evaluations and aggregating results to ensure LLM performance consistency. Learn more about this key feature.
Have a question about this repo?
These articles cover the highlights, but your codebase questions are specific. Give your agent direct access to the source. Share this with your agent to get started:
curl -s "https://instagit.com/install.md" 
Maintain an open-source project? Get it listed too →