license: cc-by-nc-4.0
language:
- te
base_model:
- facebook/mms-tts
pipeline_tag: text-to-speech
library_name: transformers
MMS Telugu Female
This model is trained using IndicTTS dataset with Telugu female speaker.
Model
mms-telugu-female-indic: Telugu model with Telugu female speaker from the IndicTTS dataset.
Sample Examples
| Text | Synthesized Audio |
|---|---|
| ఈ పనిని పూర్తి చేయడానికి రెండు రోజులు పడుతుంది. నేను మీకు సహాయం చేయగలను. | |
| ఈ పుస్తకం నాకు చాలా నచ్చింది. ఇందులో కొత్త విషయాలు చాలా ఉన్నాయి. | |
| నేను రేపు ఉదయం పది గంటలకు బయలుదేరుతాను. మీరు రాగలరా? |
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-telugu-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 Telugu model trained using a Telugu 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.