Transformers
PyTorch
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pixel
pretraining
Inference Endpoints
pixel-base / config.json
plip's picture
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{
"architectures": [
"PIXELForPreTraining"
],
"attention_probs_dropout_prob": 0.1,
"decoder_hidden_size": 512,
"decoder_intermediate_size": 2048,
"decoder_num_attention_heads": 16,
"decoder_num_hidden_layers": 8,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"image_size": [
16,
8464
],
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"mask_ratio": 0.25,
"model_type": "vit_mae",
"norm_pix_loss": true,
"num_attention_heads": 12,
"num_channels": 3,
"num_hidden_layers": 12,
"patch_size": 16,
"qkv_bias": true,
"torch_dtype": "float32",
"transformers_version": "4.17.0"
}