Instructions to use aomocelin/moonshine_tiny_pt_v06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomocelin/moonshine_tiny_pt_v06 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="aomocelin/moonshine_tiny_pt_v06")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("aomocelin/moonshine_tiny_pt_v06") model = AutoModelForSpeechSeq2Seq.from_pretrained("aomocelin/moonshine_tiny_pt_v06", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 985 Bytes
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"architectures": [
"MoonshineForConditionalGeneration"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 1,
"decoder_hidden_act": "silu",
"decoder_num_attention_heads": 8,
"decoder_num_hidden_layers": 6,
"decoder_num_key_value_heads": 8,
"decoder_start_token_id": 1,
"dtype": "float32",
"encoder_hidden_act": "gelu",
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"encoder_num_hidden_layers": 6,
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"initializer_range": 0.02,
"intermediate_size": 1152,
"is_encoder_decoder": true,
"max_position_embeddings": 194,
"model_type": "moonshine",
"pad_head_dim_to_multiple_of": 8,
"pad_token_id": 2,
"partial_rotary_factor": 0.9,
"rope_parameters": {
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"rope_theta": 10000.0,
"rope_type": "default"
},
"tie_word_embeddings": true,
"transformers_version": "5.12.1",
"use_cache": false,
"vocab_size": 32768
}
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