diff --git a/README.md b/README.md index b9f51ce..25cdbf3 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ I am able to communicate with you here and there. [![Discord](https://img.shields.io/badge/RVC%20Developers-Discord-7289DA?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/HcsmBBGyVk) -Special thanks to discord user @kalomaze#2983 for creating a temporary colab notebook for this fork. +Special thanks to discord user @kalomaze#2983 for creating a temporary colab notebook for this fork for the time being. Eventually, an official, more stable notebook will be included with this fork. Please use paperspace instead if you can as it is much more stable.
[![Open In Colab](https://img.shields.io/badge/Colab-F9AB00?style=for-the-badge&logo=googlecolab&color=525252)](https://colab.research.google.com/drive/1iWOLYE9znqT6XE5Rw2iETE19ZlqpziLx?usp=sharing) @@ -67,6 +67,9 @@ Special thanks to discord user @kalomaze#2983 for creating a temporary colab not # About this fork's crepe training: Crepe training is still incredibly instable and there's been report of a memory leak. This will be fixed in the future, however it works quite well on paperspace machines. Please note that crepe training adds a little bit of difference against a harvest trained model. Crepe sounds clearer on some parts, but sounds more robotic on some parts too. Both I would say are equally good to train with, but I still think crepe on INFERENCE is not only quicker, but more pitch stable (especially with vocal layers). Right now, its quite stable to train with a harvest model and infer it with crepe. If you are training with crepe however (f0 feature extraction), please make sure your datasets are as dry as possible to reduce artifacts and unwanted harmonics as I assume the crepe pitch estimation latches on to reverb more. +## If you get CUDA issues with crepe training, or pm and harvest etc. +This is due to the number of processes (n_p) being too high. Make sure to cut the number of threads down. Please lower the value of the "Number of CPU Threads to use" slider on the feature extraction GUI. + # Installing the Dependencies 🖥️ Using pip (python3.9.8 is stable with this fork)