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/sample1.wav from SPRINGLab/Indic-Mio: direct link, hf CLI and curl.
- Browser
- Download file 639 kB
-
https://huggingface.co/SPRINGLab/Indic-Mio/resolve/main/samples/sample1.wav
- Command line
-
hf download hf://SPRINGLab/Indic-Mio/samples/sample1.wav
-
curl -L -o sample1.wav https://huggingface.co/SPRINGLab/Indic-Mio/resolve/main/samples/sample1.wav
639 kB
- Xet hash:
- 0cdb83036a72c32859805955bc53f1c34d1afc81d53d397748dc8ea40ec4be48
- Size of remote file:
- 639 kB
- SHA256:
- 1b331f7ea55e3ded2ba9c0d8b69466d773bd28a375fcff2524a85ba1a0054402
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