Text-to-Speech
Transformers
Safetensors
qwen3
text-generation
speech
tts
voice
text-generation-inference
Instructions to use SPRINGLab/Indic-Mio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SPRINGLab/Indic-Mio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="SPRINGLab/Indic-Mio")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SPRINGLab/Indic-Mio") model = AutoModelForCausalLM.from_pretrained("SPRINGLab/Indic-Mio", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download samples/sample2.wav from SPRINGLab/Indic-Mio: direct link, hf CLI and curl.
- Browser
- Download file 1.15 MB
-
https://huggingface.co/SPRINGLab/Indic-Mio/resolve/main/samples/sample2.wav
- Command line
-
hf download hf://SPRINGLab/Indic-Mio/samples/sample2.wav
-
curl -L -o sample2.wav https://huggingface.co/SPRINGLab/Indic-Mio/resolve/main/samples/sample2.wav
1.15 MB
- Xet hash:
- 99904b103d32e582af2bd412fd3904e9e8d24ecc43107023a36a88d74f612730
- Size of remote file:
- 1.15 MB
- SHA256:
- 507f0ed0e63b502f81e6bb6e37d0b323a2292b13f72ba59832d11c5f5030b3be
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