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haoxiangsnr/
claritycec2spatial_fsb_all_codec

Name: clarity__cec2__spatial_fsb_all_codec
Availability: InStock

tensorboard

mit

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claritycec2spatial_fsb_all_codec

This project was initially created for personal use and is now archived. While the code and documentation may be incomplete, I'm happy to share it in case others find it useful.

This model was uploaded from AudioZen at 2025-01-03 05:23:11.

Overview

Training folder: /home/xhao/proj/audiozen/recipes/clarity/cec2/spatial_fsb_all_codec
Git hash: e5eb603feb2750eea1d90ce12ae596c07f292c5e

Usage

Refer to https://huggingface.co/docs/hub/en/models-downloading for instructions on how to download this model. For example, you can use the following code to download the model:

bash

# Install git lfs if you haven't already
git lfs install

# Go into the directory where you want to download the model
cd /home/xhao/proj/audiozen/recipes/clarity/cec2

# Clone the model checkpoint
git clone https://huggingface.co/haoxiangsnr/clarity__cec2__spatial_fsb_all_codec
# or
git clone git@hf.co:/haoxiangsnr/clarity__cec2__spatial_fsb_all_codec

Model Architecture

Model architecture:
Hyperparameters: Check the config.yaml file in the training folder for hyperparameters.

Environment Info

Platform: Linux-6.1.0-27-amd64-x86_64-with-glibc2.36
Python version: 3.10.16
Numpy version: 2.0.2
PyTorch version (GPU?): 2.5.1 (True)
System RAM: 503.54 GB
GPU Available: True
GPU IDs: 8
GPU type: NVIDIA GeForce RTX 3090

Note: This information was generated automatically when the model was uploaded instead of when the model was trained.

Upload Arguments

python

{
    "create_model_card": true,
    "model_folder_path": "/home/xhao/proj/audiozen/recipes/clarity/cec2/spatial_fsb_all_codec",
    "only_best_checkpoint": true,
    "only_exp_folder": false,
    "private": false
}