Transformers
PyTorch
autoformer
Inference Endpoints
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{
"activation_dropout": 0.1,
"activation_function": "gelu",
"architectures": [
"AutoformerForPrediction"
],
"attention_dropout": 0.1,
"autocorrelation_factor": 3,
"cardinality": [
366
],
"context_length": 24,
"d_model": 64,
"decoder_attention_heads": 4,
"decoder_ffn_dim": 32,
"decoder_layerdrop": 0.1,
"decoder_layers": 4,
"distribution_output": "student_t",
"dropout": 0.1,
"embedding_dimension": [
2
],
"encoder_attention_heads": 4,
"encoder_ffn_dim": 32,
"encoder_layerdrop": 0.1,
"encoder_layers": 4,
"feature_size": 22,
"init_std": 0.02,
"input_size": 1,
"label_length": 10,
"lags_sequence": [
1,
2,
3,
4,
5,
6,
7,
11,
12,
13,
23,
24,
25,
35,
36,
37
],
"loss": "nll",
"model_type": "autoformer",
"moving_average": 25,
"num_dynamic_real_features": 0,
"num_parallel_samples": 100,
"num_static_categorical_features": 1,
"num_static_real_features": 0,
"num_time_features": 2,
"prediction_length": 24,
"scaling": "mean",
"torch_dtype": "float32",
"transformers_version": "4.29.0.dev0",
"use_cache": true
}