Large-scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation
Paper • 2211.06687 • Published • 7
CLAP HTSAT-unfused — audio encoder (ONNX)
The audio encoder of laion/clap-htsat-unfused,
exported to ONNX (torch.onnx.export, opset from PyTorch 2.1). Input:
input_features (log-mel, shape [batch, 1, 1001, 64]). Output: the 512-d
L2-normalizable audio embedding. The text tower is not included.
Used by PulseMap to embed drum one-shots for a local, offline sample browser.
Provenance & license
This is a format conversion of LAION's model — the weights are unmodified, only repackaged from PyTorch to ONNX (audio tower only). All credit for the model goes to LAION. Distributed under Apache-2.0, the same license as the original. See the original model card and the CLAP paper.
Nothing in this file is trained on or derived from any private data — the drum-specific classifier that PulseMap trains on top lives in that repo, not here.
Model tree for icybawss/clap-htsat-unfused-audio-encoder-onnx
Base model
laion/clap-htsat-unfused