Merge Lora adapters with a base model
Evaluate code generation with diverse feedback types
Track, rank and evaluate open LLMs and chatbots
Evaluate reward models for math reasoning
Explore and visualize diverse models
Analyze model errors with interactive pages
Convert and upload model files for Stable Diffusion
Submit deepfake detection models for evaluation
Display LLM benchmark leaderboard and info
Explore and submit models using the LLM Leaderboard
Visualize model performance on function calling tasks
Submit models for evaluation and view leaderboard
Run benchmarks on prediction models
Merge Lora is a tool designed for model benchmarking that enables users to merge LoRA (Low-Rank Adaptation) adapters with a base model. It provides a seamless way to combine multiple adapters, enhancing the model's capabilities while maintaining efficiency. Merge Lora is particularly useful for users working with large language models and seeking to integrate specialized adapters for diverse tasks.
What is the purpose of Merge Lora?
Merge Lora is designed to simplify the process of combining LoRA adapters with a base model, allowing users to leverage specialized adapters for various tasks without retraining the model from scratch.
Can I merge multiple adapters at once?
Yes, Merge Lora supports the merging of multiple LoRA adapters into a single model, provided they are compatible.
Is Merge Lora compatible with all LoRA adapters?
While Merge Lora is designed to work with most LoRA adapters, compatibility depends on the specific adapters and base models used. Always perform a compatibility check before merging.