Instructions to use keras/whisper_tiny_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/whisper_tiny_multi with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/whisper_tiny_multi") - Keras
How to use keras/whisper_tiny_multi with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/whisper_tiny_multi") - Notebooks
- Google Colab
- Kaggle
| { | |
| "module": "keras_hub.src.models.whisper.whisper_backbone", | |
| "class_name": "WhisperBackbone", | |
| "config": { | |
| "name": "whisper_backbone", | |
| "trainable": true, | |
| "vocabulary_size": 51865, | |
| "num_layers": 4, | |
| "num_heads": 6, | |
| "hidden_dim": 384, | |
| "intermediate_dim": 1536, | |
| "num_mels": 80, | |
| "dropout": 0.0, | |
| "max_encoder_sequence_length": 3000, | |
| "max_decoder_sequence_length": 448 | |
| }, | |
| "registered_name": "keras_hub>WhisperBackbone" | |
| } |