Need of faster backend.
could anyone please provide the resources to inference on faster backend, currently it is taking 15 to 20 seconds for text with approx 10-15 words.
@Venkatesh4342 Good day. Could you please provide the code necessary to load and execute this offline, without relying on a Hugging Face repository ID? Thank you.
You can try out the IndicF5 model by cloning the repo and running the code provided in the Hugging Face model card. Here's how:
git clone https://github.com/AI4Bharat/IndicF5.git
cd IndicF5
pip install -r requirements.txt
Then, create a Python script and copy the usage example from the model card to run inference.
Let me know if you run into any issues!
@Venkatesh4342 thanks for your prompt reply, but i have tried this and is working in online mode, every time i run the inference it is hitting the hugging face, i want it to run on my local system, what i observed is the model won't load even if i provide the local path, it still treats the path as hugging face repo_id. Maybe i missed something,,,, thats where i am confused...
Downloading the model and vocab file into local folder and using that to run with T5-TTS was working but audio clarity was not same as using with huggingface might be you can try tweaking some parameters to fix it.
https://github.com/SWivid/F5-TTS?tab=readme-ov-file
Yes it generated but in my case it is giving me noise output instead of proper speech
Can you share me the code to my personal mail
on how you load the model, i tried inf5 class based loading, it seems they had defined custom class,
With Auto model also i tried but not fruitful.