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
Download tokenizer.model from VoxRT/linnet-en-35m: direct link, hf CLI and curl.
- Browser
- Download file 102 kB
-
https://huggingface.co/VoxRT/linnet-en-35m/resolve/main/tokenizer.model
- Command line
-
hf download hf://VoxRT/linnet-en-35m/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/VoxRT/linnet-en-35m/resolve/main/tokenizer.model
102 kB
- Xet hash:
- de8bdaa47c47d124a0f1e05687592833621ae19d3c78308b42161b734530ed38
- Size of remote file:
- 102 kB
- SHA256:
- 359994b0d226d0aa0b13d3a8401d6ad064ef2605b338ab7283bc64a67696850d
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