Feature Extraction
Transformers
Safetensors
audio_embeddings
audio
custom_code
self-supervised-learning
audio-embeddings
best-rq-2
audioset
Instructions to use ltuncay/BEST-RQ-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltuncay/BEST-RQ-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ltuncay/BEST-RQ-2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ltuncay/BEST-RQ-2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "AudioEmbeddingModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_audio.AudioEmbeddingConfig", | |
| "AutoModel": "modeling_audio.AudioEmbeddingModel" | |
| }, | |
| "dtype": "float32", | |
| "encoder_kwargs": { | |
| "attn_drop_rate": 0.0, | |
| "depth": 12, | |
| "drop_path_rate": 0.1, | |
| "drop_rate": 0.0, | |
| "embed_dim": 768, | |
| "mlp_ratio": 4.0, | |
| "num_heads": 12, | |
| "num_patches": 128, | |
| "pos_embed_type": "sincos", | |
| "qkv_bias": true | |
| }, | |
| "extraction_preset": "overlap50_two_phase", | |
| "feature_encoder_kwargs": {}, | |
| "hidden_size": 768, | |
| "model_target": "src.models.best_rq2_module.BestRQ2Module", | |
| "model_type": "audio_embeddings", | |
| "patch_embed_kwargs": { | |
| "embed_dim": 768, | |
| "img_size": [ | |
| 128, | |
| 256 | |
| ], | |
| "in_chans": 1, | |
| "patch_size": [ | |
| 16, | |
| 16 | |
| ] | |
| }, | |
| "sampling_rate": 16000, | |
| "spectrogram_adjustment_mode": "truncate", | |
| "spectrogram_kwargs": { | |
| "f_max": 8000, | |
| "f_min": 0, | |
| "hop_length_ms": 39.0625, | |
| "n_fft": 2048, | |
| "n_mels": 128, | |
| "power": 2.0, | |
| "sample_rate": 16000, | |
| "win_length_ms": 128 | |
| }, | |
| "transformers_version": "5.17.0" | |
| } | |