Instructions to use bezzam/MOSS-Audio-Tokenizer-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/MOSS-Audio-Tokenizer-hf with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bezzam/MOSS-Audio-Tokenizer-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,051 Bytes
0311887 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | {
"architectures": [
"MossAudioTokenizerModel"
],
"downsampling_ratios": [
240,
2,
2,
2
],
"dtype": "float32",
"hidden_sizes": [
768,
768,
768,
1280
],
"input_hidden_sizes": [
240,
768,
768,
1280
],
"intermediate_sizes": [
3072,
3072,
3072,
5120
],
"layer_scale_init_value": 0.01,
"max_position_embeddings": 2048,
"model_type": "moss_audio_tokenizer",
"num_attention_heads": [
12,
12,
12,
20
],
"num_hidden_layers": [
12,
12,
12,
32
],
"output_hidden_sizes": [
384,
384,
640,
768
],
"quantizer_config": {
"codebook_dim": 8,
"codebook_size": 1024,
"hidden_size": 512,
"input_hidden_size": 768,
"model_type": "",
"n_codebooks": 32,
"output_hidden_size": 768
},
"rope_parameters": {
"rope_theta": 10000.0,
"rope_type": "default"
},
"sampling_rate": 24000,
"sliding_window_duration": 10,
"transformers_version": "5.15.0.dev0",
"use_cache": true
}
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