Instructions to use HKUSTAudio/xcodec2-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HKUSTAudio/xcodec2-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="HKUSTAudio/xcodec2-hf")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("HKUSTAudio/xcodec2-hf") model = AutoModel.from_pretrained("HKUSTAudio/xcodec2-hf") - Notebooks
- Google Colab
- Kaggle
File size: 2,923 Bytes
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"activation_dropout": 0.1,
"architectures": [
"Xcodec2Model"
],
"attention_bias": false,
"attention_dropout": 0.0,
"downsampling_ratios": [
2,
2,
4,
4,
5
],
"dtype": "float32",
"encoder_hidden_size": 48,
"head_dim": 64,
"hidden_act": "silu",
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"max_position_embeddings": 4096,
"model_type": "xcodec2",
"num_attention_heads": 16,
"num_hidden_layers": 12,
"num_key_value_heads": 16,
"pad_token_id": null,
"quantization_dim": 2048,
"quantization_levels": [
4,
4,
4,
4,
4,
4,
4,
4
],
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 10000.0,
"rope_type": "default"
},
"sampling_rate": 16000,
"semantic_model_config": {
"_name_or_path": "facebook/w2v-bert-2.0",
"activation_dropout": 0.0,
"adapter_act": "relu",
"adapter_kernel_size": 3,
"adapter_stride": 2,
"add_adapter": false,
"apply_spec_augment": false,
"architectures": [
"Wav2Vec2BertModel"
],
"attention_dropout": 0.0,
"bos_token_id": 1,
"classifier_proj_size": 768,
"codevector_dim": 768,
"conformer_conv_dropout": 0.1,
"contrastive_logits_temperature": 0.1,
"conv_depthwise_kernel_size": 31,
"ctc_loss_reduction": "sum",
"ctc_zero_infinity": false,
"diversity_loss_weight": 0.1,
"dtype": "float32",
"eos_token_id": 2,
"feat_proj_dropout": 0.0,
"feat_quantizer_dropout": 0.0,
"feature_projection_input_dim": 160,
"final_dropout": 0.1,
"hidden_act": "swish",
"hidden_dropout": 0.0,
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"layer_norm_eps": 1e-05,
"layerdrop": 0.1,
"left_max_position_embeddings": 64,
"mask_feature_length": 10,
"mask_feature_min_masks": 0,
"mask_feature_prob": 0.0,
"mask_time_length": 10,
"mask_time_min_masks": 2,
"mask_time_prob": 0.05,
"max_source_positions": 5000,
"model_type": "wav2vec2-bert",
"num_adapter_layers": 1,
"num_attention_heads": 16,
"num_codevector_groups": 2,
"num_codevectors_per_group": 320,
"num_hidden_layers": 16,
"num_negatives": 100,
"output_hidden_size": 1024,
"pad_token_id": 0,
"position_embeddings_type": "relative_key",
"proj_codevector_dim": 768,
"right_max_position_embeddings": 8,
"rotary_embedding_base": 10000,
"tdnn_dilation": [
1,
2,
3,
1,
1
],
"tdnn_dim": [
512,
512,
512,
512,
1500
],
"tdnn_kernel": [
5,
3,
3,
1,
1
],
"use_intermediate_ffn_before_adapter": false,
"use_weighted_layer_sum": false,
"vocab_size": null,
"xvector_output_dim": 512
},
"tie_word_embeddings": false,
"transformers_version": "5.13.0.dev0"
}
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