Instructions to use Austin207/voice-fan-controller-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Austin207/voice-fan-controller-model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Austin207/voice-fan-controller-model") - Notebooks
- Google Colab
- Kaggle
File size: 1,023 Bytes
79eda24 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | {
"sample_rate_hz": 20000,
"capture_window_ms": 1600,
"n_mfcc": 20,
"n_mels": 40,
"n_fft": 512,
"hop_length": 256,
"fmin": 125,
"fmax": 7500,
"n_segments": 8,
"channels": [
"mfcc",
"delta",
"delta2"
],
"global_stats": [
"mean",
"std",
"p5",
"p95"
],
"segment_stats": [
"mean",
"std"
],
"full_dim": 1200,
"clip_sigma": 4.0,
"note": "1200 = 60 streams (20 mfcc + 20 delta + 20 delta2) x (4 global + 8*2 segment) stats",
"input_dim": 48,
"select_k": 48,
"hidden": 32,
"num_classes": 18,
"labels": [
"_silence_",
"_unknown_",
"power_on",
"power_off",
"speed_1",
"speed_2",
"speed_3",
"speed_4",
"speed_5",
"speed_6",
"mode_boost",
"mode_nature",
"mode_reverse",
"mode_smart",
"timer_off",
"timer_2h",
"timer_4h",
"timer_8h"
],
"val_float_acc": 0.9346,
"val_int8_acc": 0.9308,
"seed": 1,
"int8_bytes": 4400
} |