Instructions to use VoxRT/linnet-en-35m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LinnetTTS
How to use VoxRT/linnet-en-35m with LinnetTTS:
# pip install linnet-tts soundfile import linnet_tts, soundfile as sf from huggingface_hub import hf_hub_download model = linnet_tts.Model( hf_hub_download("VoxRT/linnet-en-35m", "linnet-en-35m.fp16.safetensors"), hf_hub_download("VoxRT/linnet-en-35m", "tokenizer.model"), ) voice = model.load_voice(hf_hub_download("VoxRT/linnet-en-35m", "voices/linnet-en-f1.npy")) audio = model.synthesize("Hello there.", voice, temp=0.3, cfg=2.0, seed=0) sf.write("hello.wav", audio, model.sample_rate) # float32, 24 kHz # streaming: one chunk per 80 ms step session = model.session(voice, seed=0) session.prime("Streaming gives the first chunk of audio after one step.") for chunk in session: ... - Notebooks
- Google Colab
- Kaggle
Commit History
10 days ago
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Linnet weights v1 (linnet-en-35m)
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