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CLAP (Contrastive Language-Audio Pretraining) is a model that learns acoustic concepts from natural language supervision and enables “Zero-Shot” inference. The model has been extensively evaluated in 26 audio downstream tasks achieving SoTA in several of them including classification, retrieval, and captioning.
<img width="832" alt="clap_diagrams" src="https://raw.githubusercontent.com/hykilpikonna/CLAP/main/docs/diagram.png">
<img width="832" alt="clap_diagrams" src="docs/clap2_diagram.png">
## Setup
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## Usage
In `CLAP\src\`:
- Zero-Shot Classification and Retrieval
```python
from msclap import CLAP
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To run Zero-Shot Classification on the ESC50 dataset try the following:
```bash
> cd src && python zero_shot_classification.py
> cd examples && python zero_shot_classification.py
```
Output (version 2023)
```bash
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