Feature Extraction
Transformers
Safetensors
English
speech_jepa
speech
audio
self-supervised-learning
jepa
speech-jepa
custom_code
Instructions to use labhamlet/speech-jepa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use labhamlet/speech-jepa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="labhamlet/speech-jepa-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("labhamlet/speech-jepa-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_config.json from labhamlet/speech-jepa-base: direct link, hf CLI and curl.
- Browser
- Download file 795 Bytes
-
https://huggingface.co/labhamlet/speech-jepa-base/resolve/main/training_config.json
- Command line
-
hf download hf://labhamlet/speech-jepa-base/training_config.json
-
curl -L -o training_config.json https://huggingface.co/labhamlet/speech-jepa-base/resolve/main/training_config.json
795 Bytes
| { | |
| "transformer_encoder_layers_cfg": { | |
| "d_model": 768, | |
| "nhead": 12, | |
| "batch_first": true, | |
| "norm_first": false, | |
| "bias": true, | |
| "dim_feedforward": 3072, | |
| "dropout": 0.0, | |
| "activation": "GELU(approximate='none')", | |
| "layer_norm_eps": 1e-06 | |
| }, | |
| "transformer_encoder_cfg": { | |
| "num_layers": 12, | |
| "enable_nested_tensor": false, | |
| "mask_check": true | |
| }, | |
| "lr": 0.0004, | |
| "adam_betas": [ | |
| 0.9, | |
| 0.98 | |
| ], | |
| "adam_eps": 1e-06, | |
| "adam_weight_decay": 0.01, | |
| "ema_decay": 0.999, | |
| "ema_end_decay": 0.99999, | |
| "ema_anneal_end_step": 100000, | |
| "warmup_steps": 100000, | |
| "average_top_k_layers": 8, | |
| "resample_sr": 16000, | |
| "original_sr": 16000, | |
| "use_gradient_checkpointing": false, | |
| "compile_modules": false, | |
| "size": "base", | |
| "clean_audio_ratio": 0.0 | |
| } |