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adding model finetuned on QA (MLQA)
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{
"_name_or_path": "CenIA/albert_xxlarge_spanish",
"architectures": [
"AlbertForQuestionAnswering"
],
"attention_probs_dropout_prob": 0,
"bos_token_id": 2,
"classifier_dropout_prob": 0.1,
"down_scale_factor": 1,
"embedding_size": 128,
"eos_token_id": 3,
"gap_size": 0,
"hidden_act": "gelu",
"hidden_dropout_prob": 0,
"hidden_size": 4096,
"initializer_range": 0.01,
"inner_group_num": 1,
"intermediate_size": 16384,
"layer_norm_eps": 1e-12,
"layers_to_keep": [],
"max_position_embeddings": 512,
"model_type": "albert",
"net_structure_type": 0,
"num_attention_heads": 64,
"num_hidden_groups": 1,
"num_hidden_layers": 12,
"num_memory_blocks": 0,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"torch_dtype": "float32",
"transformers_version": "4.15.0",
"type_vocab_size": 2,
"vocab_size": 31000
}