| # Sources |
|
|
| ## MuQ and MuQ-MuLan |
|
|
| - Paper: https://arxiv.org/abs/2501.01108 |
| - Source: https://github.com/tencent-ailab/MuQ |
| - Pinned source revision: |
| `28847ea50cd31ac4b8b6a7dacc051ad7d1c7606a` |
| - Source license: MIT |
| - Checkpoint: https://huggingface.co/OpenMuQ/MuQ-MuLan-large |
| - Pinned checkpoint revision: |
| `2e01c796b71dca71b45251384c04cd7b237c9020` |
| - Checkpoint license: CC BY-NC 4.0 |
|
|
| MuQ-MuLan is a joint music-text embedding model trained through contrastive |
| learning. Its audio and text embeddings are L2-normalized, so their dot |
| product is cosine similarity. This deployment accepts English descriptions. |
| For audio longer than 10 seconds, the official inference code embeds |
| non-overlapping 10-second windows and averages their representations. |
|
|
| ## Encoders |
|
|
| - Audio encoder: https://huggingface.co/OpenMuQ/MuQ-large-msd-iter |
| - Pinned audio revision: |
| `0562a57814f6f8bbd9fdea0a25921a2fce1a841a` |
| - Audio model license: CC BY-NC 4.0 |
| - Text encoder: https://huggingface.co/FacebookAI/xlm-roberta-base |
| - Pinned text revision: |
| `e73636d4f797dec63c3081bb6ed5c7b0bb3f2089` |
| - Text model license: MIT |
|
|
