Instructions to use naklitechie/indic-parler-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naklitechie/indic-parler-tts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="naklitechie/indic-parler-tts")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("naklitechie/indic-parler-tts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from naklitechie/indic-parler-tts: direct link, hf CLI and curl.
- Browser
- Download file 1.8 MB
-
https://huggingface.co/naklitechie/indic-parler-tts/resolve/main/tokenizer.model
- Command line
-
hf download hf://naklitechie/indic-parler-tts/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/naklitechie/indic-parler-tts/resolve/main/tokenizer.model
1.8 MB
- Xet hash:
- 611818f93a208dafc17a4fd5f2f7c3581db7b4930a496e5cad77773560c11caa
- Size of remote file:
- 1.8 MB
- SHA256:
- bc8fa773221597d09cfadb23a2b1bd717488a0481505469ea56d42cb044de9b5
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