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Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable mu...

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The problem: With long generations, volume tends to "overflow", which results in a bad quality. Possible solution: During generation, normalize volume of previously generated steps - do not allow to...

I tried 8 times waiting at least 20min, tried small and medium 5, 10, 60 and 120 sec and the loading always gets stuck Windows 10

I notice this model design is very similar to Bark. Just more efficient. Once training code is released. If pre-trained with a corpus of speech pairs, wouldn't this make a...

input: [so cute~.mp3.zip](https://github.com/facebookresearch/audiocraft/files/11876722/so.cute.mp3.zip) 2010s rock song with electric guitar and heavy drums output: [tmpflwkfvuf.mp4.zip](https://github.com/facebookresearch/audiocraft/files/11876733/tmpflwkfvuf.mp4.zip) Any suggestions regarding usage?

I am a newbie who just started to study the direction of music generation, and I have a lot of confusion about this, so I hope we can communicate with...

not sure if there is a more proper way but found that by adding to generate(), lm() and utils functions the possibility to pass a torch.generator() as argument lets me...

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Hello. I tried every different setting with MusicGen, but i still got Black windows when i generated everything like this. ![螢幕擷取畫面 (148)](https://github.com/facebookresearch/audiocraft/assets/103571045/3e318991-f2c2-488f-be0a-9bc9849b83f3) ![螢幕擷取畫面 (149)](https://github.com/facebookresearch/audiocraft/assets/103571045/07ce052e-6dde-46fc-ac78-7335028ae137) Am I missed something on installation?...

Unsure what this error is about. Is this to do with a HuggingFace token or a model called t5-base? File "C:\Users\ABC\AppData\Local\Programs\Python\Python310\lib\site-packages\filelock\_windows.py", line 25, in _acquire fd = os.open(self.lock_file, flags, self._context.mode)...

Would it be possible to use previous tokens to continue generation? and if so, how could it be implemented using the standard API (torch, audiocraft)?