pushing files to the repo from the example!

README.md

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+---
+license: apache-2.0
+library_name: sklearn
+tags:
+- sklearn
+- skops
+- tabular-classification
+model_format: pickle
+model_file: skops-rsihc7ad.pkl
+widget:
+- structuredData:
+    Age:
+    - 52
+    - 52
+    - 37
+    Annual income from social welfare programs:
+    - 0
+    - 0
+    - 0
+    Education:
+    - 5
+    - 2
+    - 3
+    Gender:
+    - 0
+    - 1
+    - 1
+    I am currently employed at least part-time:
+    - 1
+    - 1
+    - 1
+    I have a gap in my resume:
+    - 0
+    - 0
+    - 0
+    I have my regular access to the internet:
+    - 1
+    - 1
+    - 1
+    I live with my parents:
+    - 0
+    - 0
+    - 0
+    I read outside of work and school:
+    - 1
+    - 1
+    - 1
+    Income:
+    - 7
+    - 28
+    - 100
+    Lack of concentration:
+    - 0.0
+    - 0.0
+    - 0.0
+    Tiredness:
+    - 0.0
+    - 1.0
+    - 1.0
+    Unemployed:
+    - 0
+    - 0
+    - 0
+---
+
+# Model description
+
+The possible classified predictions are: 'No Mental Illness', 'Yes Mental Illness'The predictors are: 'I am currently employed at least part-time', 'Education' , 'I have my regular access to the internet', 'I live with my parents',       'I have a gap in my resume', 'Income', 'Unemployed', 'I read outside of work and school','Annual income from social welfare programs', 'Lack of concentration', 'Tiredness', 'Age', 'Gender' 
+
+## Intended uses & limitations
+
+This model follows the limitations of the Apache 2.0 license.
+
+## Training Procedure
+
+[More Information Needed]
+
+### Hyperparameters
+
+<details>
+<summary> Click to expand </summary>
+
+| Hyperparameter       | Value   |
+|----------------------|---------|
+| covariance_estimator |         |
+| n_components         |         |
+| priors               |         |
+| shrinkage            |         |
+| solver               | svd     |
+| store_covariance     | False   |
+| tol                  | 0.0001  |
+
+</details>
+
+### Model Plot
+
+<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-2" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>LinearDiscriminantAnalysis()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label sk-toggleable__label-arrow">LinearDiscriminantAnalysis</label><div class="sk-toggleable__content"><pre>LinearDiscriminantAnalysis()</pre></div></div></div></div></div>
+
+## Evaluation Results
+
+| Metric   |    Value |
+|----------|----------|
+| accuracy | 0.835821 |
+| f1 score | 0.835821 |
+
+### Model description/Evaluation Results/Classification report
+
+| index              |   precision |   recall |   f1-score |   support |
+|--------------------|-------------|----------|------------|-----------|
+| No Mental Illness  |    0.847458 | 0.961538 |   0.900901 |        52 |
+| Yes Mental Illness |    0.75     | 0.4      |   0.521739 |        15 |
+| macro avg          |    0.798729 | 0.680769 |   0.71132  |        67 |
+| weighted avg       |    0.825639 | 0.835821 |   0.816014 |        67 |
+
+# How to Get Started with the Model
+
+[More Information Needed]
+
+# Model Card Authors
+
+gianlab
+
+# Model Card Contact
+
+You can contact the model card authors through following channels:
+[More Information Needed]
+
+# Citation
+
+Below you can find information related to citation.
+
+**BibTeX:**
+```
+[More Information Needed]
+```

config.json

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+{
+    "sklearn": {
+        "columns": [
+            "I am currently employed at least part-time",
+            "Education",
+            "I have my regular access to the internet",
+            "I live with my parents",
+            "I have a gap in my resume",
+            "Income",
+            "Unemployed",
+            "I read outside of work and school",
+            "Annual income from social welfare programs",
+            "Lack of concentration",
+            "Tiredness",
+            "Age",
+            "Gender"
+        ],
+        "environment": [
+            "scikit-learn=1.2.2"
+        ],
+        "example_input": {
+            "Age": [
+                52,
+                52,
+                37
+            ],
+            "Annual income from social welfare programs": [
+                0,
+                0,
+                0
+            ],
+            "Education": [
+                5,
+                2,
+                3
+            ],
+            "Gender": [
+                0,
+                1,
+                1
+            ],
+            "I am currently employed at least part-time": [
+                1,
+                1,
+                1
+            ],
+            "I have a gap in my resume": [
+                0,
+                0,
+                0
+            ],
+            "I have my regular access to the internet": [
+                1,
+                1,
+                1
+            ],
+            "I live with my parents": [
+                0,
+                0,
+                0
+            ],
+            "I read outside of work and school": [
+                1,
+                1,
+                1
+            ],
+            "Income": [
+                7,
+                28,
+                100
+            ],
+            "Lack of concentration": [
+                0.0,
+                0.0,
+                0.0
+            ],
+            "Tiredness": [
+                0.0,
+                1.0,
+                1.0
+            ],
+            "Unemployed": [
+                0,
+                0,
+                0
+            ]
+        },
+        "model": {
+            "file": "skops-rsihc7ad.pkl"
+        },
+        "model_format": "pickle",
+        "task": "tabular-classification",
+        "use_intelex": false
+    }
+}

skops-rsihc7ad.pkl

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