clap-htsat-fused
> Contrastive learning has shown remarkable success in the field of multimodal representation learning. In this paper, we propose a pipeline of contrastive language-audio pretraining to develop an audio representation by combining audio data with natural language descriptions. To accomplish this target, we first release LAION-Audio-630K, a large collection of 633,526 audio-text pairs from different data sources. Seco...
Params
150 M
Context
—
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7.3 M
Likes
176
Download history
daily snapshots · 106 days
▲ 874 K in the last 30 days (10.7%)
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9.2 M6.1 M
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Jul 28Sep 1Oct 6Nov 10
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.6 GB | 1.2 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- ClapModel
- Parameters
- 150 M
- Tensor type
- F32
- Licence
- apache-2.0
- First seen on the Hub
- 2023-02-16
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
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