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CPU only? #1
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About the piper-tts GPU use
About fine-tuning piper ttsyou should be able to fine tune pipertts , although its much harder to lol Docs on ithttps://github.com/rhasspy/piper/blob/master/TRAINING.md Youtube Video on ithttps://www.youtube.com/watch?v=67QvWOp3dkU You say Hallucinations are the issue?
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ALSO You say you have some high quality xtts fine-tunes? 👀Slap em on hugginface, send me links to them I'll check them out ! 😄
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I can confirm the fine-tuning piper-tts colabs still work as of this moment lolI've used them before to fine tune a piper-tts model on Death from puss and boots 😅 Be aware it's very labor intensive for fine-tuning piper-tts 😭
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Perfect! Here is the first one. I'll get the rest to you later: Styletts2 was worse than Piper and xtts from my very limited experiments I just did I will have to try out that piper finetune tutorial, thanks for sharing! With the tech moving so fast, I wonder if it is worth it to dive into that now or just wait until someone makes an easy webui 😂 |
Wait how do I find the link to the Piper-tts Colab? |
Noted lolI'm uploading the newest docker image for piper tts that supports GPU! :)school wifi is slow 😅 |
The piper-tts Notebooks should be found here? 🤔 |
Hell yeah! Thanks so much, and that was crazy fast, I hope you are prioritizing your studies btw 😟
I thought you meant that there was a piper training workflow in a Google Colab 😅 I got excited lol |
Here cause school wifi is too slowDOCKER PIPER-TTS GPUdocker run -it --gpus all -p 7860:7860 --platform=linux/amd64 registry.hf.space/drewthomasson-ebook2audiobookpiper-tts-gpu:latest python app.py You can also duplicate the hugginface space if you want to give it a gpu from huggingface at like 40 cents an hour lolhttps://huggingface.co/spaces/drewThomasson/ebook2audiobookpiper-tts-GPU |
Woah! Great, thank you!
🔥🔥🔥🔥🔥🔥🔥🔥🔥 |
Hmm, still having trouble getting Piper to work with GPU
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Do you have a Cuda capable Nvida GPU? cause it only works with Nvidia GPU's What output do you get when you run this? docker run --gpus all nvidia/cuda:11.0-base nvidia-smi |
Here, I tried fixing it by addingnvidia-cuda-toolkit
libcudnn8
libcudnn8-dev
libegl1
libopengl0
libxcb-cursor0 into the packages.txt for the huggingface space Try again with this comand to make it force pull the latest docker image and see if this works ✨docker run -it --gpus all -p 7860:7860 --platform=linux/amd64 --pull always registry.hf.space/drewthomasson-ebook2audiobookpiper-tts-gpu:latest python app.py
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Hm, I tried the new pull and still not working, also the Colab says notebook not found I am on Windows 10, RTX 3090
Does it have to be v11? If it is confirmed to work on Colab it must be something on my end that I can troubleshoot. |
OP you right, here try this for the google colab now I gave the wrong linkOr this: |
Were you able to confirm in the Colab that it was using the GPU, not the CPU? I don't have Colab Pro so I can't check |
The updated pull runs fine on my computer btw, not sure that wasn't clear. But it still uses the CPU instead of my 3090 |
wait I think your right >:| I'll try another method and see what happens |
I got that result running this test script in google colab !pip install piper-tts
!pip install onnxruntime-gpu
import subprocess
import time
start_time = time.time()
subprocess.run(
"echo 'Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!' | piper --model en_US-lessac-medium --output_file welcome.wav --cuda True",
shell=True
)
end_time = time.time()
duration = end_time - start_time
print(f"GPU CUDA Command took {duration:.2f} seconds to run.")
import subprocess
import time
start_time = time.time()
subprocess.run(
"echo 'Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!Welcome to the world of speech synthesis I am a bot!' | piper --model en_US-lessac-medium --output_file welcome.wav",
shell=True
)
end_time = time.time()
duration = end_time - start_time
print(f"CPU Command took {duration:.2f} seconds to run.")
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Nevermind it appears to be broken lol The files produced by the GPU were actually empty So >:| |
I'm putting this on hold, As it doesn't appear to be possible Hit me up if you get piper itself running on your computer tho utilizing the GPU Cause I can't figure it out for the life of me Wouldn't even have to be modifying my code all I'd need is some example of any line of code that runs on GPU :( |
lol thanks for trying, I will give it a go and see if I can make any headway. CPU speeds are workable, I am just curious to see how much faster it is using GPU 😄 |
Same lol I can't Seem to find any definitive answer of it online for how much faster it is :/ |
Well update: i found this space looks like it might be able to use the gpu? https://huggingface.co/spaces/Gregniuki/Pipertts When I Duplicated the space on gpu it seemed to work for me hmmm but GPU didn't seem that much faster . . . which is odd you could attempt at running it locally as a docker perhaps? here is my gpu duplicate version that should work on your computer as a docker docker run -it -p 7860:7860 --platform=linux/amd64 \
-e HF_TOKEN="YOUR_VALUE_HERE" \
registry.hf.space/drewthomasson-pipertts:latest |
Do tell if you see it utilizing your GPU tho if you test it out :) |
Hm, can't get the webui to open I tried pretty hard to change some files around with the original ebook2audiobook package but kept running into Docker build problems when installing 😑 Maybe I will try a little more, I feel like I am close. Would be interesting if it ends up that the CPU version is faster for some reason 😶 |
I tried a bunch of stuff and couldn't get it to work.. sigh.. ur guys' job is hard I will move on to trying out Piper finetunes! |
https://huggingface.co/spaces/Gregniuki/Pipertts/discussions/1#672c0972b28c400174cb6e43 Ok so getting somewhere 👀 |
Ok SO WE HAVE An ANSWER ON SPEED INCREASE From the guy:
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Nice! I tried adapting his app code, changing the onnxruntime-gpu version, torch etc. for my 3090 to no avail. lol it feels so doable but I haven't had any luck. Curious to see what kind of performance he was getting in his experiments. Thanks for keeping the dream alive |
Oh just saw your update! That's a massive increase! Dang that is so tantalizing especially because my card is so much faster than the 1050 |
It seems to be running in CPU only, even though I used this prompt to start it in Docker:
docker run -it --rm --gpus all -p 7860:7860 athomasson2/ebook2audiobookpiper-tts:latest
Am I doing something wrong? Looks like it is possible based on this thread:
rhasspy/wyoming-piper#5
Thanks!
ps. While I found that xtts has better phrasing, the hallucinations (made up words, vocal artifacts) are worse than Piper which make the narration harder to understand unfortunately. I tried messing with a lot of the advanced settings (temperature etc. but couldn't get xtts more consistent than the base settings).
I am excited for Piper finetuning btw! Is there a way to be notified when finetuning is available? Also, I have made some high quality xxts finetunes, I would be happy to send them to you to attach to the project if you want. Just let me know!
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