onecxi/mms-hindi-female-indic

MMS Hindi Female

This model is trained using IndicTTS dataset with Hindi female speaker.

Model

mms-hindi-female-indic: Hindi model with Hindi female speaker from the IndicTTS dataset.

Sample Examples

Inference

To use these models for inference, you'll need to install the transformers and accelerate libraries.

First, install the necessary libraries:

pip install --upgrade transformers accelerate

Then, run inference with the following code-snippet:

from transformers import VitsModel, AutoTokenizer
import torch
from IPython.display import Audio

model_path = "onecxi/mms-hindi-female-indic" # This is the path to your fine-tuned model
model = VitsModel.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)

text = "This is a Hindi model trained using a Hindi female speaker."
inputs = tokenizer(text, return_tensors="pt")

with torch.no_grad():
    output = model(**inputs).waveform

Audio(output.numpy(), rate=model.config.sampling_rate)

Disclaimer

This Text-to-Speech (TTS) model is intended solely for research and educational use. Any use of the model must comply with all applicable laws, regulations, and ethical standards. The unauthorized use of this model for impersonating real individuals without their explicit consent is strictly prohibited. Additionally, the model must not be used to create or distribute deceptive, misleading, or fraudulent content, including but not limited to fake news or scams. Any use of the model for illegal, harmful, or malicious purposes is expressly forbidden.

By using this model, you acknowledge and agree to these terms. The creators and distributors of the model disclaim any liability for misuse and do not support or condone unethical or unlawful applications.