51–60 of 245 posts
How fast is inference with this model? For reference, I'm using 11Labs to synthesize short messages - maybe a sentence or something, using voice cloning, and I'm getting it at around 400 - 500ms response times. Is there any OS solution that gets me to around the same inference time?
Was somewhat annoying to get everything to work as the documentation is a bit spotty, but after ~20 minutes it's all working well for me on WSL Ubuntu 22.04. Sound quality is very good, much better than other open source TTS projects I've seen. It's also SUPER fast (at least using a 4090 GPU). Not sure it's quite up to Eleven Labs quality. But to me, what makes Eleven so cool is that they have a large library of high…
I really want to try this but making the venv to install all the torch dependencies is starting to get old lol. How are other people dealing with this? Is there an easy way to get multiple venvs to share like a common torch venv? I can do this manually but I'm wondering if there's a tool out there that does this.
Was somewhat annoying to get everything to work as the documentation is a bit spotty, but after ~20 minutes it's all working well for me on WSL Ubuntu 22.04. Sound quality is very good, much better than other open source TTS projects I've seen. It's also SUPER fast (at least using a 4090 GPU). Not sure it's quite up to Eleven Labs quality. But to me, what makes Eleven so cool is that they have a large library of high…
Was somewhat annoying to get everything to work as the documentation is a bit spotty, but after ~20 minutes it's all working well for me on WSL Ubuntu 22.04. Sound quality is very good, much better than other open source TTS projects I've seen. It's also SUPER fast (at least using a 4090 GPU). Not sure it's quite up to Eleven Labs quality. But to me, what makes Eleven so cool is that they have a large library of high…
I really want to try this but making the venv to install all the torch dependencies is starting to get old lol. How are other people dealing with this? Is there an easy way to get multiple venvs to share like a common torch venv? I can do this manually but I'm wondering if there's a tool out there that does this.
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A Mac with a lot of unified RAM can do it, or a dual 3090/4090 setup gets you 48gb of VRAM.
I’ve got a 64gb Mac M2. All of the openllm models seem to hang on startup or on API calls. I got them working through GCP colab. Not sure if it’s a configuration issue or if the hardware just isn’t up to it?
Funnily enough, the TTS2 examples sound better than the ground truth [0]. For example, the "Then leaving the corpse within the house [...]" example has the ground truth pronounce "house" weirdly, with some change in the tonality that sounds higher, but the TTS2 version sounds more natural. I'm excited to use this for all my ePub files, many of which don't have corresponding audiobooks, such as a lot of Japanese light…
Impressive results nonetheless, and superior to all other TTS.
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how are you planning on using this with epubs? i'm in a similar boat. would really like to leverage something like this for ebooks.
I wonder if you can add a TTS engine to Android as an app or plugin, then make Moon+ Reader or another reader to use that custom engine. That's probably how I'd do it for the easiest approach, but if that doesn't work, I might just have to make my own app.