commit files to HF hub
Browse files- README.md +52 -0
- config.json +36 -0
- images/algebra.jpg +0 -0
- images/arithmetic.jpg +0 -0
- images/calculus.jpg +0 -0
- images/geometry.jpg +0 -0
- images/trigonometry.jpg +0 -0
- preprocessor_config.json +17 -0
- pytorch_model.bin +3 -0
- runs/events.out.tfevents.1641604117.08939beddcba.73.0 +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: rare-puppers
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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: 0.4895833432674408
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---
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# rare-puppers
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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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#### algebra
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![algebra](images/algebra.jpg)
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#### arithmetic
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![arithmetic](images/arithmetic.jpg)
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#### calculus
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![calculus](images/calculus.jpg)
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#### geometry
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![geometry](images/geometry.jpg)
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#### trigonometry
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![trigonometry](images/trigonometry.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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"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": "algebra",
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"1": "arithmetic",
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"2": "calculus",
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"3": "geometry",
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"4": "trigonometry"
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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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"algebra": "0",
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"arithmetic": "1",
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"calculus": "2",
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"geometry": "3",
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"trigonometry": "4"
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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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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.15.0"
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}
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images/algebra.jpg
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images/arithmetic.jpg
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images/calculus.jpg
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images/geometry.jpg
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images/trigonometry.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:bfe5aa1d93b6d69b98e95946a4c8d6349d06795d308473d4b2d34a790c2c65ca
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size 343286257
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runs/events.out.tfevents.1641604117.08939beddcba.73.0
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:31e4eb756888e071eaf5a1426b4ea608596dbc90e1fb1eb56030358676f8742a
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size 1351
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