minor changes

faq/rvc/rvc.md

@@ -43,7 +43,7 @@ An Epoch is the number of iterations performed during training to complete one f
 
 - **Rmvpe:** Model with Crepe and PM features, fast and quality tone processing with low probability of distortion.
 
-- **FPCE:** Fpce is a alternative hybrid method that works similarly to f0 with the difference of a slightly more optimized processing and taking less context from the input audio for a "particular" conversion.
+- **Fcpe:** Fpce is a alternative hybrid method that works similarly to f0 with the difference of a slightly more optimized processing and taking less context from the input audio for a "particular" conversion.
 
 ==-
 ==- Batch Size

get-started/Alternatives.md

@@ -33,7 +33,7 @@ Google Colab **(Google Colaboratory)** is a free cloud based platform that enabl
 
  3. You can [train](/get-started\training.md/) models while checking [Tensorboard](/get-started\tensorboard.md), do [inference](/get-started\inferencing.md/), or use [TTS](/get-started\tts.md/)
 
- ### How to upload my dataset in Colab?
+ ### 4. How to upload my dataset in Colab?
  To load your dataset in Colab, there are two ways to do it:
 
  - Place your audio in a folder on your Google Drive, run the **Mount Drive** cell in Colab and click on :file_folder: in Colab. Then navigate to your dataset folder, copy the path, it should look like this `/content/drive/MyDrive/dataset folder` and paste it into the **dataset path**.
@@ -42,9 +42,32 @@ Google Colab **(Google Colaboratory)** is a free cloud based platform that enabl
 
  !!!info Mark the **Save Only Latest** option before training to prevent it from filling up your Colab storage.
  !!!
- 4. Click on :file_folder: in Colab and locate your trained model in the `program/logs/model` folder, and the .pth files are in the `program/logs/zips` folder. If you want to save your model folder in your Drive, you just need to run the **Mount Drive** and **AutoBackup** cell before run **Start Applio** cell.
 
- -  (If you want to retrain place the name of your model in the **Load a Backup** cell and run it. Then, insert the name of your model and enter a higher number of epochs)
+ ### 5. How to export my model to my Google Drive?
+ To save your model, there are two ways to do it:
+ - **Finished Model:** go to the **Export Model** section in the **Train** tab, click on the **Refresh** button and select the pth and the added index of the model to export. Finally, click on the **Upload** button, your model will be found in the **ApplioExported** folder ready to be used.
+
+ - **Model to continue training:** if you want to save all the archives of your model folder in your Drive, you just need to run the **Mount Drive** and **AutoBackup** cell before run **Start Applio** cell, your model folder will be found inside the **ApplioBackup** folder.
+
+ (If you want to retrain place the name of your model in the **Load a Backup** cell and run it. Then, insert the name of your model and enter a higher number of epochs)
+
+ ### Code to be afk
+
+ To run this code in Colab, we have to press the keys **Ctrl + Shift + i** to open the **developer tools** option and the following window will open. In case another window is displayed, we can locate it by selecting the **Console** option, so in this way Colab will not disconnect during the separation process. First, we put **Allow pasting**, then we press enter and only then it will let us enter the code.
+
+ ``` js
+ function ClickConnect() {
+ var iconElement = document.getElementById("toggle-header-button");
+ if (iconElement) {
+ var clickEvent = new MouseEvent ("click", {
+ bubbles: true, cancelable: true,
+ view: window
+ });
+ iconElement.dispatchEvent (clickEvent);
+ }
+ }
+ setInterval(ClickConnect, 6000);
+```
 +++ Huggingface
 ## What is Huggingface?
 Hugging Face is a company specialized in artificial intelligence that has distinguished itself through its work in developing tools and models for **natural language processing (NLP)**. This has made it one of the leading online communities and platforms for cutting edge NLP model research, development and distribution.

get-started/inferencing.md

@@ -6,12 +6,12 @@ order: B
 
 # Infer & Download models
 
-- Downloading a [voice model](/voice-models) is as simple as going to the **"download"** tab.
+- Downloading a [voice model](/voice-models) is as simple as going to the **Download** tab.
 
-![**Manual loading alternative:** unzip the downloaded .zip file and **drag the two files into the corresponding box below.**](/assets/download_models.png)
+![**Manual loading alternative:** unzip the downloaded .zip file and **drag the two files into the Drop files box**. Now you can search for models from Applio by simply entering the character name to search in the **Search Model** section, then copy the model link or download it.](/assets/download_models.png)
 
 !!!warning
-Downloading files from mega may fail!, this is due to malfunction of the dependency.
+Applio can only download models from Google Drive, Huggingface, [Applio Web](https://applio.org/models), Discord, Yandex, Pixeldrain and Mediafire. Downloading files from mega may fail!, this is due to malfunction of the dependency.
 !!!
 
 ---
@@ -32,9 +32,10 @@ Downloading files from mega may fail!, this is due to malfunction of the depende
 
 !!!primary Make sure the path and audio name don't contain spaces or special characters.
 !!!
-- **Recommendation:** having a **clean acapella** helps to get better results. but if the model downloaded in its name mentions the words rvmpe, crepe or mangio-crepe click on the **advanced options box**. Furthermore, this section has the following:
+- **Recommendation:** having a **clean acapella** helps to get better results. but if the model downloaded in its name mentions the words rvmpe or crepe click on the **advanced options box**. Furthermore, this section has the following:
 
 ==- **Advanced Settings**
+- **Export Format:** Select the format to export the audio.
 - **Split Audio:** Basically cuts the audio into parts to make the inference by parts and then joins them together.
 - **Autotune:** Apply a soft autotune to your inferences, recommended for singing conversions.
 - **Clean Audio:** Clean your audio output using noise detection algorithms, recommended for speaking audios.
@@ -45,7 +46,7 @@ Downloading files from mega may fail!, this is due to malfunction of the depende
 - **Volume Envelope:** Substitute or blend with the volume envelope of the output.
 - **Protec Voiceless Consonants:** Safeguard distinct consonants and breathing sounds to prevent electro-acoustic tearing and other artifacts.
 - **Hop Length:** Denotes the duration it takes for the system to transition to a significant pitch change. Smaller hop lengths require more time for inference and training but tend to yield higher pitch accuracy.
-- **Pitch extraction algorithm:** Select between [rvmpe, crepe, mangio-crepe or other](https://docs.applio.org/faq/rvc/#f0-extraction-methods)
+- **Pitch extraction algorithm:** Select between [rvmpe, crepe or other](https://docs.applio.org/faq/rvc/#f0-extraction-methods)
 ==- 
 
 !!!primary What should I do if my output audio sounds [robotic](https://docs.applio.org/faq/rvc/#artifacting)?

get-started/pretrained.md

@@ -13,10 +13,13 @@ Those are pretraineds trained by AI enthusiasts, unlike the original pretraineds
 
 ### Download [Ov2Super](https://huggingface.co/ORVC/Ov2Super/tree/main) by SimPLClup
 ### Download [RIN_E3](https://huggingface.co/MUSTAR/RIN_E3/tree/main) by mustar22
+### Download SnowieV3 [32k](https://huggingface.co/MUSTAR/SnowieV3.1-32k/tree/main), [40K](https://huggingface.co/MUSTAR/SnowieV3.1-40k/tree/main), [48K](https://huggingface.co/MUSTAR/SnowieV3.1-48k/tree/main) by mustar22
+### Download [SnowieV3 X RIN_E3](https://huggingface.co/MUSTAR/SnowieV3.1-X-RinE3-40K/tree/main) by mustar22
 
 !!!info Things you should know:
-- **Ov2Super** works well for small datasets. Additionally, it allows models to train with very few epochs compared to regular pretrains. This only supports 32k and 40k sample rates 
-- **RIN_E3** yields good results with clean datasets, but it is more sensitive to noise, this only support 40k 
-sample rate.
+- **Ov2Super** works well for small and english datasets. Additionally, it allows models to train with very few epochs compared to regular pretrains. This only supports **32k and 40k** sample rates 
+- **RIN_E3** yields good results with clean and english datasets, but it is more sensitive to noise, this only support **40k** sample rate.
+- **SnowieV3** works well with Russian datasets, and also helps models of other languages to pronounce Russian well, this support **all the sample rates**.
+- **SnowieV3 X RIN_E3** works well with Russian or Japanese language datasets, and also helps models of other languages to pronounce Russian or Japanese well, this only support **40k** sample rate.
 - Make sure to select the sample rate according to the sample rate of the custom pretraineds.
 !!!

get-started/training.md

@@ -64,6 +64,9 @@ Once configured, press **_'Start training'_** to start the process, everything i
 1. Once training is completed, generate the index file by clicking the "Train Feature Index" button.
 |||
 
+!!!info
+Now you can export your trained model directly from the Applio interface, go to the **Export Model** section in the **train** tab, click on the **Refresh** button and select the **pth and the [added index](https://docs.applio.org/faq/rvc/#added-index)** of the model to export.
+!!!
 
 - (If you want to retrain, enter the same name of the model and locate in which stage the save files are left, enter a higher number of [epoch](https://docs.applio.org/faq/rvc/#epoch).)
 

get-started/tts.md

@@ -9,7 +9,7 @@ icon: typography
 
 - Select our **model with its respective index**.
 
-- Select the **model of TTS** depending on the language you want and enter the text to convert.
+- Select the **model of TTS** depending on the language you want and enter the text or add a **txt file** in the box below to convert.
 
 - Finally we click on **convert** and wait for the result
 -![](/assets/TTS.png)-

guides/Audio/UVR.md

@@ -52,7 +52,7 @@ You can change the **type of wav or the MP3 bitrate** in **Additional settings**
 
 2. In our Google Drive, we created the folder **Separar** where we will put our songs to separate, and **Vocales** where our already separated song will be stored.
 !!!info
-Now you can download the music that you want to separate from Colab. go to the **YouTube Audio Downloader for Separation** cell, just place the link of the song in **video_url** and run that cell. Your song will be stored in the folders that you created in your Drive.
+Now you can download the music that you want to separate from Colab, go to the **YouTube Audio Downloader for Separation** cell, just place the link of the song in **video_url** and song name in **audio_name**, then run that cell. Your song will be stored in the **Separar** folder that you created in your Drive.
 !!!
 3. Run the **Installation** cell to start cloning the repository to the colab and mount drive.
 
@@ -81,6 +81,6 @@ Now you can download the music that you want to separate from Colab. go to the *
 - If you wish, you can change the **Segment Size** and the **Overlap** in case of **MDX23C** and **MDX-NET**, the **windows size** and the **aggression setting** for **VR Arc** to your preference or leave it as it is.
 !!!
 
-5. Now we go to the **Vocals folder**, there we find our separate audios, we download the audio with the name of the **song-Vocals**, in case you want the instrumental is **song-Instrumental**.
+5. Now we go to the **Vocales folder**, there we find our separate audios, we download the audio with the name of the **song-Vocals**, in case you want the instrumental is **song-Instrumental**.
 :::
 +++ 

voice-models/Web.md

@@ -8,3 +8,5 @@ order: B
 If you are not closely related to discord or some other reason you can choose to use **[the web version of the Applio](https://applio.org/)**, search for any RVC voice model in our database.
 
 ![](/assets/Applio_Website.png)
+
+- Choose the model you wish to use and click on :icon-copy: to get the link or on :icon-download: to download it, then go to the [Download](/get-started\inferencing.md) tab of Applio.