Update README.md

README.md

@@ -1,3 +1,81 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+- contrastive learning
+- CLAP
+- audio classification
+- zero-shot classification
+---
+
+# tinyCLAP: Distilling Contrastive Language-Audio Pretrained models
+
+[![arXiv](https://img.shields.io/badge/arXiv-1234.56789-b31b1b.svg)](https://arxiv.org/abs/2311.14517)
+
+This repository contains the official implementation of [tinyCLAP](https://arxiv.org/abs/2311.14517).
+
+![tinyCLAP overview](https://francescopaissan.it/tinyclapweb/assets/overview.png)
+
+## Requirements
+
+To install requirements:
+
+```setup
+pip install -r extra_requirements.txt
+```
+
+## Training
+
+To train the model(s) in the paper, run this command:
+
+```bash
+MODEL_NAME=phinet_alpha_1.50_beta_0.75_t0_6_N_7
+
+./run_tinyCLAP.sh $MODEL_NAME
+```
+
+Note that `MODEL_NAME` is formatted such that the script will automatically parse the configuration for the student model.
+You can change parameters by changing the model name.
+
+Please note:
+- To use the original CLAP encoder in the distillation setting, replace the model name with `Cnn14`;
+- To reproduce the variants of PhiNet from the manuscript, refer to the hyperparameters listed in Table 1.
+
+## Evaluation
+
+The command to evaluate the model on each dataset varies slightly among datasets.
+Below are listed all the necessary commands.
+
+### ESC50
+
+```bash
+python train_clap.py --experiment_name tinyCLAP_$MODEL_NAME --zs_eval True --esc_folder $PATH_TO_ESC
+```
+
+### UrbanSound8K
+
+```bash
+python train_clap.py --experiment_name tinyCLAP_$MODEL_NAME --zs_eval True --us8k_folder $PATH_TO_US8K
+```
+
+### TUT17
+
+```bash
+python train_clap.py --experiment_name tinyCLAP_$MODEL_NAME --zs_eval True --tut17_folder $PATH_TO_TUT17
+```
+
+## Pre-trained Models
+
+You can download pretrained models here:
+
+- [My awesome model](https://drive.google.com/mymodel.pth) trained on ImageNet using parameters x,y,z.
+
+## Citing tinyCLAP
+
+```
+@inproceedings{paissan2024tinyclap,
+  title={tinyCLAP: Distilling Constrastive Language-Audio Pretrained Models},
+  author={Paissan, Francesco and Farella, Elisabetta},
+  journal={Interspeech 2024},
+  year={2024}
+}
+```