commit files to HF hub
Browse files- .gitattributes +24 -0
- README.md +128 -0
- config.json +76 -0
- images/A.jpg +3 -0
- images/B.jpg +3 -0
- images/C.jpg +3 -0
- images/D.jpg +3 -0
- images/E.jpg +3 -0
- images/F.jpg +3 -0
- images/G.jpg +3 -0
- images/H.jpg +3 -0
- images/I.jpg +3 -0
- images/K.jpg +3 -0
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- images/O.jpg +3 -0
- images/P.jpg +3 -0
- images/Q.jpg +3 -0
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- images/S.jpg +3 -0
- images/T.jpg +3 -0
- images/U.jpg +3 -0
- images/V.jpg +3 -0
- images/W.jpg +3 -0
- images/X.jpg +3 -0
- images/Y.jpg +3 -0
- preprocessor_config.json +22 -0
- pytorch_model.bin +3 -0
- runs/events.out.tfevents.1672605952.e853388a7406 +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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images/A.jpg filter=lfs diff=lfs merge=lfs -text
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images/B.jpg filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags:
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- image-classification
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- pytorch
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- huggingpics
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metrics:
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- accuracy
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model-index:
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- name: Sign-Language
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results:
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- task:
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name: Image Classification
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type: image-classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 1.0
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---
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# Sign-Language
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Autogenerated by HuggingPics🤗🖼️
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Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
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Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
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## Example Images
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#### A
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![A](images/A.jpg)
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#### B
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![B](images/B.jpg)
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#### C
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![C](images/C.jpg)
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#### D
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![D](images/D.jpg)
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#### E
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![E](images/E.jpg)
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#### F
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![F](images/F.jpg)
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#### G
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![G](images/G.jpg)
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#### H
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![H](images/H.jpg)
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#### I
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![I](images/I.jpg)
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#### K
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![K](images/K.jpg)
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#### L
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![L](images/L.jpg)
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#### M
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![M](images/M.jpg)
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#### N
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![N](images/N.jpg)
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#### O
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![O](images/O.jpg)
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#### P
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![P](images/P.jpg)
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#### Q
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![Q](images/Q.jpg)
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#### R
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![R](images/R.jpg)
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#### S
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![S](images/S.jpg)
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#### T
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![T](images/T.jpg)
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#### U
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![U](images/U.jpg)
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#### V
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![V](images/V.jpg)
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#### W
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![W](images/W.jpg)
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#### X
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![X](images/X.jpg)
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#### Y
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![Y](images/Y.jpg)
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "A",
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"1": "B",
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"10": "L",
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"11": "M",
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"12": "N",
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"13": "O",
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"14": "P",
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"15": "Q",
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"16": "R",
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"17": "S",
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"18": "T",
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"19": "U",
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"2": "C",
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"20": "V",
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"21": "W",
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"22": "X",
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"23": "Y",
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"3": "D",
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"4": "E",
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"5": "F",
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"6": "G",
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"7": "H",
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"8": "I",
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"9": "K"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"A": "0",
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"B": "1",
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"C": "2",
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"D": "3",
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"E": "4",
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"F": "5",
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"G": "6",
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"H": "7",
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"I": "8",
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"K": "9",
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"L": "10",
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"M": "11",
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"N": "12",
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"O": "13",
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"P": "14",
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"Q": "15",
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"R": "16",
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"S": "17",
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"T": "18",
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"U": "19",
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"V": "20",
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"W": "21",
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"X": "22",
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"Y": "23"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.25.1"
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}
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images/A.jpg
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Git LFS Details
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images/B.jpg
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Git LFS Details
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images/C.jpg
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Git LFS Details
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images/D.jpg
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images/E.jpg
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images/F.jpg
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Git LFS Details
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images/G.jpg
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images/H.jpg
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images/I.jpg
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images/K.jpg
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images/L.jpg
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images/M.jpg
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images/N.jpg
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images/O.jpg
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images/P.jpg
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images/Q.jpg
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images/R.jpg
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Git LFS Details
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images/S.jpg
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Git LFS Details
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images/T.jpg
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images/U.jpg
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Git LFS Details
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images/V.jpg
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Git LFS Details
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images/W.jpg
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Git LFS Details
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images/X.jpg
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Git LFS Details
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images/Y.jpg
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Git LFS Details
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTImageProcessor",
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"image_std": [
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0.5,
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}
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pytorch_model.bin
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