commit files to HF hub
Browse files- README.md +56 -0
- config.json +40 -0
- images/blue_color.jpg +0 -0
- images/cyan_color.jpg +0 -0
- images/green_color.jpg +0 -0
- images/orange_color.jpg +0 -0
- images/red_color.jpg +0 -0
- images/yellow_color.jpg +0 -0
- preprocessor_config.json +17 -0
- pytorch_model.bin +3 -0
- runs/events.out.tfevents.1649743971.38bbaf15b7b0.74.0 +3 -0
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: blocks
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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: 0.4444444477558136
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---
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# blocks
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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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#### blue color
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![blue color](images/blue_color.jpg)
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#### cyan color
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![cyan color](images/cyan_color.jpg)
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#### green color
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![green color](images/green_color.jpg)
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#### orange color
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![orange color](images/orange_color.jpg)
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#### red color
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![red color](images/red_color.jpg)
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#### yellow color
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![yellow color](images/yellow_color.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": "blue color",
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"1": "cyan color",
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"2": "green color",
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"3": "orange color",
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"4": "red color",
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"5": "yellow color"
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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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"blue color": "0",
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"cyan color": "1",
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"green color": "2",
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"orange color": "3",
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"red color": "4",
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"yellow color": "5"
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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": "4.18.0"
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}
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images/blue_color.jpg
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images/cyan_color.jpg
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images/green_color.jpg
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images/orange_color.jpg
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images/red_color.jpg
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images/yellow_color.jpg
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "ViTFeatureExtractor",
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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_std": [
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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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"resample": 2,
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"size": 224
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:56fae0caf7a319eb88f535e494fa38621947eb25d40d002e9d22425a7da7c081
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size 343276465
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runs/events.out.tfevents.1649743971.38bbaf15b7b0.74.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:0cba85e60b99c92176b2c55dd282425d1020fc623b25283f12d1b17b5d4936a5
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size 881
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