Guide users through the lmms-eval codebase for Large Multimodal Models.
npx skills add https://github.com/jayaylee/PromPrune --skill lmms-eval-guide
Please help me install this Agent Skill. Skill: lmms-eval-guide Source: https://github.com/jayaylee/PromPrune/tree/main/lmms-eval/skills/lmms-eval-guide Command: npx skills add https://github.com/jayaylee/PromPrune --skill lmms-eval-guide
This Skill provides a comprehensive guide to the lmms-eval codebase, simplifying the process of integrating new models, adding evaluation tasks, and running complex evaluations for Large Multimodal Models (LMMs).
Use the lmms-eval-guide skill to understand how to add a new model backend to the lmms-eval framework.
High-intent search queries and answers about installing and using this skill.
You can use the lmms-eval framework's CLI or HTTP API server to execute evaluation pipelines. This Skill guides users through the specific CLI operations and API server usage required to run complex evaluations for Large Multimodal Models.
Task definition in lmms-eval involves specifying the evaluation metrics, dataset loaders, and processing logic required for Large Multimodal Models. This Skill helps you navigate the codebase architecture to understand and define custom evaluation tasks.
Yes, the lmms-eval framework supports both CLI operations and an HTTP API server for executing evaluation pipelines. This Skill details how to utilize the HTTP API server to manage complex evaluation setups and optimize performance.
The best way to navigate the lmms-eval codebase is by understanding its key components for model integration, task definition, and pipeline execution. This Skill facilitates codebase navigation, helping advanced users manage complex setups and debug workflows.
Debugging evaluation workflows in lmms-eval requires understanding the pipeline execution logic and model integration points. This Skill supports advanced users by providing guidance on debugging workflows and optimizing evaluation performance for Large Multimodal Models.
EvolvingLMMs-LabGuide AI coding agents through the lmms-eval codebase for LMM evaluation.
surus-latMerge local benchmark results into the HuggingFace LatamBoard leaderboard dataset.
eddieluengFilter, deduplicate, and redact large-scale multimodal datasets with GPU acceleration.
davpatel605-beepEvaluate LLMs against standardized benchmarks like MMLU and GSM8K.
