# EvA: An Evidence-First Audio Understanding Paradigm for LALMs  

## Environment Setup  
You can either refer to **Kimi-Audio** for environment preparation, or simply use the provided `requirements.txt` file.  

## Quick Start  
Run `test_inference.py` to quickly verify the setup and start inference.  

## Training  
1. Specify the model path in `finetune_codes/model.py`.  
2. Pre-tokenize audio with `finetune_codes/extract_semantic_codes.py` to accelerate training.  
3. Start fine-tuning with either:  
   - `finetune_codes/finetune_ds.sh`  
   - `finetune_codes/finetune_lora.sh`  

## Evaluation & Reference  
- Ensure the model path is correctly set in `finetune_codes/model.py`.  
- Use `scripts/dataset_inf.sh` to evaluate performance on diverse benchmarks, and align the dataset format with the Kimi-Audio input.  
