Text-to-Speech
Safetensors
Pocket-TTS
English
candle
tts
int8
quantized
wasm
8-bit precision
channel_wise_int8
Instructions to use idle-intelligence/pocket-tts-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Pocket-TTS
How to use idle-intelligence/pocket-tts-int8 with Pocket-TTS:
from pocket_tts import TTSModel import scipy.io.wavfile tts_model = TTSModel.load_model("idle-intelligence/pocket-tts-int8") voice_state = tts_model.get_state_for_audio_prompt( "hf://kyutai/tts-voices/alba-mackenna/casual.wav" ) audio = tts_model.generate_audio(voice_state, "Hello world, this is a test.") # Audio is a 1D torch tensor containing PCM data. scipy.io.wavfile.write("output.wav", tts_model.sample_rate, audio.numpy()) - Notebooks
- Google Colab
- Kaggle
Download quantize_config.json from idle-intelligence/pocket-tts-int8: direct link, hf CLI and curl.
- Browser
- Download file 324 Bytes
-
https://huggingface.co/idle-intelligence/pocket-tts-int8/resolve/main/quantize_config.json
- Command line
-
hf download hf://idle-intelligence/pocket-tts-int8/quantize_config.json
-
curl -L -o quantize_config.json https://huggingface.co/idle-intelligence/pocket-tts-int8/resolve/main/quantize_config.json
324 Bytes
| { | |
| "quant_method": "channel_wise_int8", | |
| "bits": 8, | |
| "format": "per_output_channel_scale", | |
| "weight_dtype": "I8", | |
| "scale_dtype": "BF16", | |
| "description": "Each weight tensor 'foo' is stored as I8 values in 'foo' with a BF16 per-output-channel scale in 'foo_scale'. Dequantize: weight_bf16 = weight_i8 * scale_bf16." | |
| } | |