FreqFault-base
Inference checkpoint for the base FreqFault time-frequency encoder.
| Item | Value |
|---|---|
| Time embedding dimension | 128 |
| Frequency embedding dimension | 128 |
| Fused feature dimension | 256 |
| Attention heads | 4 |
| Layers per branch | 4 |
| Parameters | 1.67M |
| Weight size | 6.69 MB |
| Frequency bins | 800 |
| Input window | 0.1 seconds |
Usage
import numpy as np
import torch
from model import UniFreqProcessor, load_model
model, config = load_model("bojian1/FreqFault-base")
batch = UniFreqProcessor(config)([
np.random.randn(2048).astype("float32")
])
with torch.inference_mode():
features = model(batch)
Inference code and documentation: https://github.com/Bojian-Chen/FreqFault
This repository contains inference artifacts only: config.json and
model.safetensors.
The repository was renamed from bojian1/UniFreq-base. Python API names
(UniFreqProcessor, UniFreqModel) and architecture identifiers remain
compatible with existing code. Model weights are unchanged.