Instructions to use yd97/whisper_fine_tuning_lr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use yd97/whisper_fine_tuning_lr with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("yd97/whisper_fine_tuning_lr", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from yd97/whisper_fine_tuning_lr: direct link, hf CLI and curl.
- Browser
- Download file 339 Bytes
-
https://huggingface.co/yd97/whisper_fine_tuning_lr/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://yd97/whisper_fine_tuning_lr/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/yd97/whisper_fine_tuning_lr/resolve/main/preprocessor_config.json
339 Bytes
| { | |
| "chunk_length": 30, | |
| "feature_extractor_type": "WhisperFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 160, | |
| "n_fft": 400, | |
| "n_samples": 480000, | |
| "nb_max_frames": 3000, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "WhisperProcessor", | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |