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
File size: 4,071 Bytes
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"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"
} |