Instructions to use nineninesix/kani-tts-400m-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nineninesix/kani-tts-400m-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="nineninesix/kani-tts-400m-de")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nineninesix/kani-tts-400m-de") model = AutoModelForCausalLM.from_pretrained("nineninesix/kani-tts-400m-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8802bb7f891be554bc81fe640ad68ab0e4e9afbbc11cdb61d92868ea089ff105
- Size of remote file:
- 740 MB
- SHA256:
- e1c64cad5ee8eab209b609bb885e1ed27600fbd292f2eb5c001cc6dca3352094
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