Instructions to use keras/moonshine_tiny_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/moonshine_tiny_en with KerasHub:
import keras_hub # Create a Seq2SeqLM model task = keras_hub.models.Seq2SeqLM.from_preset("hf://keras/moonshine_tiny_en")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/moonshine_tiny_en") - Keras
How to use keras/moonshine_tiny_en 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/moonshine_tiny_en") - Notebooks
- Google Colab
- Kaggle
| { | |
| "module": "keras_hub.src.models.moonshine.moonshine_audio_to_text", | |
| "class_name": "MoonshineAudioToText", | |
| "config": { | |
| "backbone": { | |
| "module": "keras_hub.src.models.moonshine.moonshine_backbone", | |
| "class_name": "MoonshineBackbone", | |
| "config": { | |
| "name": "moonshine_backbone_1", | |
| "trainable": true, | |
| "vocabulary_size": 32768, | |
| "filter_dim": 288, | |
| "encoder_num_layers": 6, | |
| "decoder_num_layers": 6, | |
| "hidden_dim": 288, | |
| "intermediate_dim": 1152, | |
| "encoder_num_heads": 8, | |
| "decoder_num_heads": 8, | |
| "feedforward_expansion_factor": 4, | |
| "encoder_use_swiglu_activation": false, | |
| "decoder_use_swiglu_activation": true, | |
| "max_position_embeddings": 194, | |
| "pad_head_dim_to_multiple_of": null, | |
| "partial_rotary_factor": 0.9, | |
| "dropout": 0.0, | |
| "initializer_range": 0.02, | |
| "rope_theta": 10000.0, | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "dtype": "float32" | |
| }, | |
| "registered_name": "keras_hub>MoonshineBackbone" | |
| }, | |
| "preprocessor": { | |
| "module": "keras_hub.src.models.moonshine.moonshine_audio_to_text_preprocessor", | |
| "class_name": "MoonshineAudioToTextPreprocessor", | |
| "config": { | |
| "name": "moonshine_audio_to_text_preprocessor_1", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "float32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "tokenizer": { | |
| "module": "keras_hub.src.models.moonshine.moonshine_tokenizer", | |
| "class_name": "MoonshineTokenizer", | |
| "config": { | |
| "name": "moonshine_tokenizer_1", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "int32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "config_file": "tokenizer.json", | |
| "proto": null, | |
| "sequence_length": null, | |
| "add_bos": false, | |
| "add_eos": false | |
| }, | |
| "registered_name": "keras_hub>MoonshineTokenizer" | |
| }, | |
| "audio_converter": { | |
| "module": "keras_hub.src.models.moonshine.moonshine_audio_converter", | |
| "class_name": "MoonshineAudioConverter", | |
| "config": { | |
| "name": "moonshine_audio_converter_1", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "float32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "sampling_rate": 16000, | |
| "padding_value": 0.0, | |
| "do_normalize": false | |
| }, | |
| "registered_name": "keras_hub>MoonshineAudioConverter" | |
| }, | |
| "config_file": "preprocessor.json" | |
| }, | |
| "registered_name": "keras_hub>MoonshineAudioToTextPreprocessor" | |
| }, | |
| "name": "moonshine_audio_to_text_1" | |
| }, | |
| "registered_name": "keras_hub>MoonshineAudioToText" | |
| } |