a little massage

README.md

@@ -1,6 +1,5 @@
 # VoiceCraft: Zero-Shot Speech Editing and Text-to-Speech in the Wild
-[Demo](https://jasonppy.github.io/VoiceCraft_web) [Paper](https://jasonppy.github.io/assets/pdfs/VoiceCraft.pdf)
-
+[![Paper](https://img.shields.io/badge/arXiv-2301.12503-brightgreen.svg?style=flat-square)](https://jasonppy.github.io/assets/pdfs/VoiceCraft.pdf)  [![githubio](https://img.shields.io/badge/GitHub.io-Audio_Samples-blue?logo=Github&style=flat-square)](https://jasonppy.github.io/VoiceCraft_web/)  [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/pyp1/VoiceCraft_gradio)  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1IOjpglQyMTO2C3Y94LD9FY0Ocn-RJRg6?usp=sharing)
 
 ### TL;DR
 VoiceCraft is a token infilling neural codec language model, that achieves state-of-the-art performance on both **speech editing** and **zero-shot text-to-speech (TTS)** on in-the-wild data including audiobooks, internet videos, and podcasts.
@@ -8,20 +7,22 @@ VoiceCraft is a token infilling neural codec language model, that achieves state
 To clone or edit an unseen voice, VoiceCraft needs only a few seconds of reference.
 
 ## How to run inference
-There are three ways:
+There are three ways (besides running Gradio in Colab):
 
-1. with Google Colab. see [quickstart colab](#quickstart-colab)
+1. More flexible inference beyond Gradio UI in Google Colab. see [quickstart colab](#quickstart-colab)
 2. with docker. see [quickstart docker](#quickstart-docker)
-3. without docker. see [environment setup](#environment-setup)
+3. without docker. see [environment setup](#environment-setup). You can also run gradio locally if you choose this option
 
 When you are inside the docker image or you have installed all dependencies, Checkout [`inference_tts.ipynb`](./inference_tts.ipynb).
 
 If you want to do model development such as training/finetuning, I recommend following [envrionment setup](#environment-setup) and [training](#training).
 
 ## News
-:star: 03/28/2024: Model weights for giga330M and giga830M are up on HuggingFace🤗 [here](https://huggingface.co/pyp1/VoiceCraft/tree/main)!
+:star: 04/11/2024: VoiceCraft Gradio is now available on HuggingFace Spaces [here](https://huggingface.co/spaces/pyp1/VoiceCraft_gradio)! Major thanks to [@zuev-stepan](https://github.com/zuev-stepan), [@Sewlell](https://github.com/Sewlell), [@pgsoar](https://github.com/pgosar) [@Ph0rk0z](https://github.com/Ph0rk0z). 
 
-:star: 04/05/2024: I finetuned giga330M with the TTS objective on gigaspeech and 1/5 of librilight, the model outperforms giga830M on TTS. Weights are [here](https://huggingface.co/pyp1/VoiceCraft/tree/main). Make sure maximal prompt + generation length <= 16 seconds (due to our limited compute, we had to drop utterances longer than 16s in training data)
+:star: 04/05/2024: I finetuned giga330M with the TTS objective on gigaspeech and 1/5 of librilight. Weights are [here](https://huggingface.co/pyp1/VoiceCraft/tree/main). Make sure maximal prompt + generation length <= 16 seconds (due to our limited compute, we had to drop utterances longer than 16s in training data). Even stronger models forthcomming, stay tuned!
+
+:star: 03/28/2024: Model weights for giga330M and giga830M are up on HuggingFace🤗 [here](https://huggingface.co/pyp1/VoiceCraft/tree/main)!
 
 ## TODO
 - [x] Codebase upload
@@ -30,9 +31,12 @@ If you want to do model development such as training/finetuning, I recommend fol
 - [x] Training guidance
 - [x] RealEdit dataset and training manifest
 - [x] Model weights (giga330M.pth, giga830M.pth, and gigaHalfLibri330M_TTSEnhanced_max16s.pth)
-- [x] Write colab notebooks for better hands-on experience
-- [ ] HuggingFace Spaces demo
-- [ ] Better guidance on training/finetuning
+- [x] Better guidance on training/finetuning
+- [x] Colab notebooks
+- [x] HuggingFace Spaces demo
+- [ ] Command line
+- [ ] Improve efficiency
+
 
 
 ## QuickStart Colab
@@ -109,7 +113,7 @@ Checkout [`inference_speech_editing.ipynb`](./inference_speech_editing.ipynb) an
 ## Gradio
 ### Run in colab
 
-[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/zuev-stepan/VoiceCraft-gradio/blob/feature/colab-notebook/voicecraft-gradio-colab.ipynb)
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1IOjpglQyMTO2C3Y94LD9FY0Ocn-RJRg6?usp=sharing)
 
 ### Run locally
 After environment setup install additional dependencies:

gradio_app.py

@@ -13,7 +13,7 @@ import random
 import uuid
 
 
-DEMO_PATH = os.getenv("DEMO_PATH", ".demo")
+DEMO_PATH = os.getenv("DEMO_PATH", "./demo")
 TMP_PATH = os.getenv("TMP_PATH", "./demo/temp")
 MODELS_PATH = os.getenv("MODELS_PATH", "./pretrained_models")
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -371,20 +371,20 @@ demo_original_transcript = " But when I had approached so near to them, the comm
 
 demo_text = {
     "TTS": {
-        "smart": "I cannot believe that the same model can also do text to speech synthesis as well!",
-        "regular": "But when I had approached so near to them, the common I cannot believe that the same model can also do text to speech synthesis as well!"
+        "smart": "I cannot believe that the same model can also do text to speech synthesis too!",
+        "regular": "But when I had approached so near to them, the common I cannot believe that the same model can also do text to speech synthesis too!"
     },
     "Edit": {
         "smart": "saw the mirage of the lake in the distance,",
         "regular": "But when I saw the mirage of the lake in the distance, which the sense deceives, Lost not by distance any of its marks,"
     },
     "Long TTS": {
-        "smart": "You can run TTS on a big text!\n"
+        "smart": "You can run the model on a big text!\n"
                  "Just write it line-by-line. Or sentence-by-sentence.\n"
-                 "If some sentences sound odd, just rerun TTS on them, no need to generate the whole text again!",
-        "regular": "But when I had approached so near to them, the common You can run TTS on a big text!\n"
+                 "If some sentences sound odd, just rerun the model on them, no need to generate the whole text again!",
+        "regular": "But when I had approached so near to them, the common You can run the model on a big text!\n"
                    "But when I had approached so near to them, the common Just write it line-by-line. Or sentence-by-sentence.\n"
-                   "But when I had approached so near to them, the common If some sentences sound odd, just rerun TTS on them, no need to generate the whole text again!"
+                   "But when I had approached so near to them, the common If some sentences sound odd, just rerun the model on them, no need to generate the whole text again!"
     }
 }
 
@@ -602,9 +602,9 @@ if __name__ == "__main__":
 
     parser = argparse.ArgumentParser(description="VoiceCraft gradio app.")
     
-    parser.add_argument("--demo-path", default=".demo", help="Path to demo directory")
-    parser.add_argument("--tmp-path", default=".demo/temp", help="Path to tmp directory")
-    parser.add_argument("--models-path", default=".pretrained_models", help="Path to voicecraft models directory")
+    parser.add_argument("--demo-path", default="./demo", help="Path to demo directory")
+    parser.add_argument("--tmp-path", default="./demo/temp", help="Path to tmp directory")
+    parser.add_argument("--models-path", default="./pretrained_models", help="Path to voicecraft models directory")
     parser.add_argument("--port", default=7860, type=int, help="App port")
     parser.add_argument("--share", action="store_true", help="Launch with public url")
 

voicecraft-gradio-colab.ipynb

@@ -18,7 +18,7 @@
       },
       "outputs": [],
       "source": [
-        "!git clone https://github.com/zuev-stepan/VoiceCraft-gradio"
+        "!git clone https://github.com/jasonppy/VoiceCraft"
       ]
     },
     {