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VicentCano
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toki-pona-asr-wav2vec2-xls-r-300m

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
toki pona
asr
xls-r
Inference Endpoints
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1
toki-pona-asr-wav2vec2-xls-r-300m
File size: 2,078 Bytes 
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{
  "_name_or_path": "VicentCano/toki_pona_asr_wav2vec2-xls-r-300m",
  "activation_dropout": 0.0,
  "adapter_kernel_size": 3,
  "adapter_stride": 2,
  "add_adapter": false,
  "apply_spec_augment": true,
  "architectures": [
    "Wav2Vec2ForCTC"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 1,
  "classifier_proj_size": 256,
  "codevector_dim": 768,
  "contrastive_logits_temperature": 0.1,
  "conv_bias": true,
  "conv_dim": [
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  ],
  "conv_kernel": [
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  ],
  "conv_stride": [
    5,
    2,
    2,
    2,
    2,
    2,
    2
  ],
  "ctc_loss_reduction": "mean",
  "ctc_zero_infinity": false,
  "diversity_loss_weight": 0.1,
  "do_stable_layer_norm": true,
  "eos_token_id": 2,
  "feat_extract_activation": "gelu",
  "feat_extract_dropout": 0.0,
  "feat_extract_norm": "layer",
  "feat_proj_dropout": 0.0,
  "feat_quantizer_dropout": 0.0,
  "final_dropout": 0.0,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout": 0.0,
  "hidden_size": 1024,
  "initializer_range": 0.02,
  "intermediate_size": 4096,
  "layer_norm_eps": 1e-05,
  "layerdrop": 0.0,
  "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,
  "model_type": "wav2vec2",
  "num_adapter_layers": 3,
  "num_attention_heads": 16,
  "num_codevector_groups": 2,
  "num_codevectors_per_group": 320,
  "num_conv_pos_embedding_groups": 16,
  "num_conv_pos_embeddings": 128,
  "num_feat_extract_layers": 7,
  "num_hidden_layers": 24,
  "num_negatives": 100,
  "output_hidden_size": 1024,
  "pad_token_id": 18,
  "proj_codevector_dim": 768,
  "tdnn_dilation": [
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  ],
  "tdnn_dim": [
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  ],
  "tdnn_kernel": [
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  ],
  "torch_dtype": "float32",
  "transformers_version": "4.28.1",
  "use_weighted_layer_sum": false,
  "vocab_size": 21,
  "xvector_output_dim": 512
}