Instructions to use Shanos76/f5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- F5-TTS
How to use Shanos76/f5 with F5-TTS:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-4.0
library_name: f5-tts
datasets:
- SPRINGLab/IndicTTS-Hindi
- SPRINGLab/IndicVoices-R_Hindi
language:
- hi
pipeline_tag: text-to-speech
widget:
- text: >-
उसके दोस्त, प्रेमिकाएँ, और रिश्तेदार, उसे इसी नाम से बुलाते थे, और वो भी,
अक्सर समझ जाता था, कि क्वैं उसी को संबोधित है
output:
url: samples/output1.wav
- text: >-
इस बागीचे में, आप शुरू से अन्त तक घूम आइये, तो दुनिया भर की सुन्दर चीज़ों
के साथ, एक अनन्यता महसूस करेंगें
output:
url: samples/output2.wav
- text: >-
शिवगढ़ी गाँव, एक बड़ा गाँव था, और उसमेँ सबसे बड़ा मकान, पण्डित दुर्गाशङ्कर
श्रीमुख का था
output:
url: samples/output3.wav
F5-TTS Hindi 24KHz Model
This is a Hindi Text-to-Speech model trained from scratch using the F5 architecture.
Details
- Developed by: SPRING Lab, Indian Institute of Technology, Madras
- Language: Hindi
- License: CC-BY-4.0
Uses
The model was developed and is primarily intended for research purposes.
How to Get Started with the Model
Clone the following github repo and refer to the README: https://github.com/rumourscape/F5-TTS
Training Details
The model was trained on 8x A100 40GB GPUs for close to a week. We would like to thank CDAC for providing the compute resources.
We used the "small" configuration(151M parameter) model for training according to the F5 paper.
Training Data
We used the Hindi subsets of IndicTTS and IndicVoices-R datasets for training this model.
- IndicTTS-Hindi: https://huggingface.co/datasets/SPRINGLab/IndicTTS-Hindi
- IndicVoices-R_Hindi: https://huggingface.co/datasets/SPRINGLab/IndicVoices-R_Hindi