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@@ -4,9 +4,6 @@ tags:
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  - keras
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  pipeline_tag: image-to-text
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  ---
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- ---
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- license: mit
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- ---
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  ```
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  API_URL = "https://api-inference.huggingface.co/models/CIS-5190-CIA/Ensamble"
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@@ -17,17 +14,21 @@ client = InferenceClient(
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      token="TOKEN HERE",
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  )
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  ```
 
 
 
 
 
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  ```
 
 
 
 
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  lat_mean = 39.95173281562989
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  lat_std = 0.0006925131397316982
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  lon_mean = -75.19143805846498
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  lon_std = 0.0006552266653111098
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  ```
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- # Run Instructions:
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-
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- ## Unpack the Ensamble models
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- Use the following file to unpickle our model: Run_Ensemble.ipynb \
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- It loads the model from Huggingface and the only thing that they need to update is the directory location of the testing dataset
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  ## Helper Functions to Predict from & Evaluate Ensamble
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  These functions will allow you to use the ensamble to predict and evaluate the model
 
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  - keras
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  pipeline_tag: image-to-text
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  ---
 
 
 
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  ```
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  API_URL = "https://api-inference.huggingface.co/models/CIS-5190-CIA/Ensamble"
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      token="TOKEN HERE",
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  )
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  ```
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+
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+ ## How to Run
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+ In the notebook Run_ensamble.ipynb, replace the line:
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+ ```python
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+ dataset_test = load_dataset("gydou/released_img")
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  ```
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+ with the proper location of the testing dataset.
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+
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+ ## Training Dataset Statistics
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+ ```python
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  lat_mean = 39.95173281562989
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  lat_std = 0.0006925131397316982
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  lon_mean = -75.19143805846498
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  lon_std = 0.0006552266653111098
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  ```
 
 
 
 
 
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  ## Helper Functions to Predict from & Evaluate Ensamble
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  These functions will allow you to use the ensamble to predict and evaluate the model