Transformers
TensorBoard
Safetensors
vit_mae
pretraining
masked-auto-encoding
Generated from Trainer
Instructions to use crncskn/prtrnlng2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crncskn/prtrnlng2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForPreTraining processor = AutoImageProcessor.from_pretrained("crncskn/prtrnlng2") model = AutoModelForPreTraining.from_pretrained("crncskn/prtrnlng2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 675 Bytes
8e40efb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"architectures": [
"ViTMAEForPreTraining"
],
"attention_probs_dropout_prob": 0.0,
"decoder_hidden_size": 512,
"decoder_intermediate_size": 2048,
"decoder_num_attention_heads": 16,
"decoder_num_hidden_layers": 8,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_size": 768,
"image_size": 224,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"mask_ratio": 0.75,
"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": "4.40.0.dev0"
}
|