Add Vision Transformer for landmark classification

README.md

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+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
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+### Model Sources [optional]
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+<!-- Provide the basic links for the model. -->
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+- **Repository:** [More Information Needed]
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+## Uses
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+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+### Direct Use
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+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+[More Information Needed]
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+### Downstream Use [optional]
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+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+### Out-of-Scope Use
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+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+## Bias, Risks, and Limitations
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+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+[More Information Needed]
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+### Recommendations
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+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
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+## Training Details
+
+### Training Data
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+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+[More Information Needed]
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+### Training Procedure
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+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
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+[More Information Needed]
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+
+#### Training Hyperparameters
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+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
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+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+[More Information Needed]
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+## Evaluation
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+<!-- This section describes the evaluation protocols and provides the results. -->
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+### Testing Data, Factors & Metrics
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+#### Testing Data
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+<!-- This should link to a Dataset Card if possible. -->
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+[More Information Needed]
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+#### Factors
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+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+[More Information Needed]
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+#### Metrics
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+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+[More Information Needed]
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+### Results
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+#### Summary
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+
+
+## Model Examination [optional]
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+<!-- Relevant interpretability work for the model goes here -->
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+[More Information Needed]
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+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
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+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
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+[More Information Needed]
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+### Compute Infrastructure
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+[More Information Needed]
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+#### Hardware
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+[More Information Needed]
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+#### Software
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+## Citation [optional]
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+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+**BibTeX:**
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+**APA:**
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+## Glossary [optional]
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+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+[More Information Needed]
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+## More Information [optional]
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+[More Information Needed]
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+## Model Card Authors [optional]
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+[More Information Needed]
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+## Model Card Contact
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+[More Information Needed]

config.json

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+{
+  "_name_or_path": "landmark-classification-vit",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Haleakala National Park",
+    "1": "Mount Rainier National Park",
+    "2": "Ljubljana Castle",
+    "3": "Dead Sea",
+    "4": "Wroclaws Dwarves",
+    "5": "London Olympic Stadium",
+    "6": "Niagara Falls",
+    "7": "Stonehenge",
+    "8": "Grand Canyon",
+    "9": "Golden Gate Bridge",
+    "10": "Edinburgh Castle",
+    "11": "Mount Rushmore National Memorial",
+    "12": "Kantanagar Temple",
+    "13": "Yellowstone National Park",
+    "14": "Terminal Tower",
+    "15": "Central Park",
+    "16": "Eiffel Tower",
+    "17": "Changdeokgung",
+    "18": "Delicate Arch",
+    "19": "Vienna City Hall",
+    "20": "Matterhorn",
+    "21": "Taj Mahal",
+    "22": "Moscow Raceway",
+    "23": "Externsteine",
+    "24": "Soreq Cave",
+    "25": "Banff National Park",
+    "26": "Pont du Gard",
+    "27": "Seattle Japanese Garden",
+    "28": "Sydney Harbour Bridge",
+    "29": "Petronas Towers",
+    "30": "Brooklyn Bridge",
+    "31": "Washington Monument",
+    "32": "Hanging Temple",
+    "33": "Sydney Opera House",
+    "34": "Great Barrier Reef",
+    "35": "Monumento a la Revolucion",
+    "36": "Badlands National Park",
+    "37": "Atomium",
+    "38": "Forth Bridge",
+    "39": "Gateway of India",
+    "40": "Stockholm City Hall",
+    "41": "Machu Picchu",
+    "42": "Death Valley National Park",
+    "43": "Gullfoss Falls",
+    "44": "Trevi Fountain",
+    "45": "Temple of Heaven",
+    "46": "Great Wall of China",
+    "47": "Prague Astronomical Clock",
+    "48": "Whitby Abbey",
+    "49": "Temple of Olympian Zeus"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Atomium": 37,
+    "Badlands National Park": 36,
+    "Banff National Park": 25,
+    "Brooklyn Bridge": 30,
+    "Central Park": 15,
+    "Changdeokgung": 17,
+    "Dead Sea": 3,
+    "Death Valley National Park": 42,
+    "Delicate Arch": 18,
+    "Edinburgh Castle": 10,
+    "Eiffel Tower": 16,
+    "Externsteine": 23,
+    "Forth Bridge": 38,
+    "Gateway of India": 39,
+    "Golden Gate Bridge": 9,
+    "Grand Canyon": 8,
+    "Great Barrier Reef": 34,
+    "Great Wall of China": 46,
+    "Gullfoss Falls": 43,
+    "Haleakala National Park": 0,
+    "Hanging Temple": 32,
+    "Kantanagar Temple": 12,
+    "Ljubljana Castle": 2,
+    "London Olympic Stadium": 5,
+    "Machu Picchu": 41,
+    "Matterhorn": 20,
+    "Monumento a la Revolucion": 35,
+    "Moscow Raceway": 22,
+    "Mount Rainier National Park": 1,
+    "Mount Rushmore National Memorial": 11,
+    "Niagara Falls": 6,
+    "Petronas Towers": 29,
+    "Pont du Gard": 26,
+    "Prague Astronomical Clock": 47,
+    "Seattle Japanese Garden": 27,
+    "Soreq Cave": 24,
+    "Stockholm City Hall": 40,
+    "Stonehenge": 7,
+    "Sydney Harbour Bridge": 28,
+    "Sydney Opera House": 33,
+    "Taj Mahal": 21,
+    "Temple of Heaven": 45,
+    "Temple of Olympian Zeus": 49,
+    "Terminal Tower": 14,
+    "Trevi Fountain": 44,
+    "Vienna City Hall": 19,
+    "Washington Monument": 31,
+    "Whitby Abbey": 48,
+    "Wroclaws Dwarves": 4,
+    "Yellowstone National Park": 13
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.1"
+}

model.safetensors

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