pushing files to the repo from the example!

README.md

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+---
+license: mit
+library_name: sklearn
+tags:
+- sklearn
+- skops
+- tabular-classification
+model_format: pickle
+model_file: model.pkl
+widget:
+  structuredData:
+    petal length (cm):
+    - 5.7
+    - 5.6
+    - 5.2
+    petal width (cm):
+    - 2.1
+    - 2.4
+    - 2.0
+    sepal length (cm):
+    - 6.7
+    - 6.3
+    - 6.5
+    sepal width (cm):
+    - 3.3
+    - 3.4
+    - 3.0
+---
+
+# Model description
+
+[More Information Needed]
+
+## Intended uses & limitations
+
+[More Information Needed]
+
+## Training Procedure
+
+[More Information Needed]
+
+### Hyperparameters
+
+<details>
+<summary> Click to expand </summary>
+
+| Hyperparameter    | Value   |
+|-------------------|---------|
+| C                 | 1.0     |
+| class_weight      |         |
+| dual              | False   |
+| fit_intercept     | True    |
+| intercept_scaling | 1       |
+| l1_ratio          |         |
+| max_iter          | 100     |
+| multi_class       | auto    |
+| n_jobs            |         |
+| penalty           | l2      |
+| random_state      | 0       |
+| solver            | lbfgs   |
+| tol               | 0.0001  |
+| verbose           | 0       |
+| warm_start        | False   |
+
+</details>
+
+### Model Plot
+
+<style>#sk-container-id-4 {color: black;background-color: white;}#sk-container-id-4 pre{padding: 0;}#sk-container-id-4 div.sk-toggleable {background-color: white;}#sk-container-id-4 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-4 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-4 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-4 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-4 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-4 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-item {position: relative;z-index: 1;}#sk-container-id-4 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-4 div.sk-item::before, #sk-container-id-4 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-4 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-4 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-4 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-4 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-4 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-4 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-4 div.sk-label-container {text-align: center;}#sk-container-id-4 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-4 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-4" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>LogisticRegression(random_state=0)</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-4" type="checkbox" checked><label for="sk-estimator-id-4" class="sk-toggleable__label sk-toggleable__label-arrow">LogisticRegression</label><div class="sk-toggleable__content"><pre>LogisticRegression(random_state=0)</pre></div></div></div></div></div>
+
+## Evaluation Results
+
+| Metric   |    Value |
+|----------|----------|
+| accuracy | 0.933333 |
+| f1 score | 0.933333 |
+
+# How to Get Started with the Model
+
+[More Information Needed]
+
+# Model Card Authors
+
+This model card is written by following authors:
+
+[More Information Needed]
+
+# 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]
+```
+
+# citation_bibtex
+
+bibtex
+@inproceedings{...,year={2020}}
+
+# get_started_code
+
+import pickle 
+with open(dtc_pkl_filename, 'rb') as file: 
+    clf = pickle.load(file)
+
+# model_card_authors
+
+skops_user
+
+# limitations
+
+This model is not ready to be used in production.
+
+# model_description
+
+This is a DecisionTreeClassifier model trained on breast cancer dataset.
+
+# eval_method
+
+The model is evaluated using test split, on accuracy and F1 score with macro average.

config.json

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+{
+    "sklearn": {
+        "columns": [
+            "sepal length (cm)",
+            "sepal width (cm)",
+            "petal length (cm)",
+            "petal width (cm)"
+        ],
+        "environment": [
+            "scikit-learn=1.1.1"
+        ],
+        "example_input": {
+            "petal length (cm)": [
+                5.7,
+                5.6,
+                5.2
+            ],
+            "petal width (cm)": [
+                2.1,
+                2.4,
+                2.0
+            ],
+            "sepal length (cm)": [
+                6.7,
+                6.3,
+                6.5
+            ],
+            "sepal width (cm)": [
+                3.3,
+                3.4,
+                3.0
+            ]
+        },
+        "model": {
+            "file": "model.pkl"
+        },
+        "model_format": "pickle",
+        "task": "tabular-classification",
+        "use_intelex": false
+    }
+}

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:137aed0449bf9e92a2377635d279166d96276002057d55f659e162dd53641fb4
+size 994