Ekjaer commited on
Commit
d760ca3
·
1 Parent(s): 0c2e2ed

pushing files to the repo from the example!

Browse files
README.md CHANGED
@@ -4,7 +4,7 @@ tags:
4
  - sklearn
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  - skops
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  - tabular-classification
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- model_file: skops-8nefprdu.pkl
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  widget:
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  structuredData:
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  area error:
@@ -188,7 +188,7 @@ The model is trained with below hyperparameters.
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189
  The model plot is below.
190
 
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- <style>#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f {color: black;background-color: white;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f pre{padding: 0;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-toggleable {background-color: white;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f 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-0c1d7c13-a4c8-4590-87aa-1f83604d531f 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-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-estimator:hover {background-color: #d4ebff;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-item {z-index: 1;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-parallel::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-parallel-item:only-child::after {width: 0;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f 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;position: relative;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-label-container {position: relative;z-index: 2;text-align: center;}#sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f 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-0c1d7c13-a4c8-4590-87aa-1f83604d531f div.sk-text-repr-fallback {display: none;}</style><div id="sk-0c1d7c13-a4c8-4590-87aa-1f83604d531f" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>HalvingGridSearchCV(estimator=HistGradientBoostingClassifier(), n_jobs=-1,param_grid={&#x27;max_depth&#x27;: [2, 5, 10],&#x27;max_leaf_nodes&#x27;: [5, 10, 15]},random_state=42)</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="fda069f1-3c89-4cdd-93a3-300250ad04ac" type="checkbox" ><label for="fda069f1-3c89-4cdd-93a3-300250ad04ac" class="sk-toggleable__label sk-toggleable__label-arrow">HalvingGridSearchCV</label><div class="sk-toggleable__content"><pre>HalvingGridSearchCV(estimator=HistGradientBoostingClassifier(), n_jobs=-1,param_grid={&#x27;max_depth&#x27;: [2, 5, 10],&#x27;max_leaf_nodes&#x27;: [5, 10, 15]},random_state=42)</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="f08bbe7b-c0ba-40eb-983c-ca33a0c7f783" type="checkbox" ><label for="f08bbe7b-c0ba-40eb-983c-ca33a0c7f783" class="sk-toggleable__label sk-toggleable__label-arrow">HistGradientBoostingClassifier</label><div class="sk-toggleable__content"><pre>HistGradientBoostingClassifier()</pre></div></div></div></div></div></div></div></div></div></div>
192
 
193
  ## Evaluation Results
194
 
@@ -207,7 +207,7 @@ Use the code below to get started with the model.
207
  import joblib
208
  import json
209
  import pandas as pd
210
- clf = joblib.load(skops-8nefprdu.pkl)
211
  with open("config.json") as f:
212
  config = json.load(f)
213
  clf.predict(pd.DataFrame.from_dict(config["sklearn"]["example_input"]))
 
4
  - sklearn
5
  - skops
6
  - tabular-classification
7
+ model_file: skops-r1ync5kc.pkl
8
  widget:
9
  structuredData:
10
  area error:
 
188
 
189
  The model plot is below.
190
 
191
+ <style>#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d {color: black;background-color: white;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d pre{padding: 0;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-toggleable {background-color: white;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d 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-5c3d3891-7051-4361-8cf7-97673b45eb4d 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-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-estimator:hover {background-color: #d4ebff;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-item {z-index: 1;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-parallel::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-parallel-item:only-child::after {width: 0;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d 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;position: relative;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-label-container {position: relative;z-index: 2;text-align: center;}#sk-5c3d3891-7051-4361-8cf7-97673b45eb4d 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-5c3d3891-7051-4361-8cf7-97673b45eb4d div.sk-text-repr-fallback {display: none;}</style><div id="sk-5c3d3891-7051-4361-8cf7-97673b45eb4d" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>HalvingGridSearchCV(estimator=HistGradientBoostingClassifier(), n_jobs=-1,param_grid={&#x27;max_depth&#x27;: [2, 5, 10],&#x27;max_leaf_nodes&#x27;: [5, 10, 15]},random_state=42)</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="ee8c16da-5d99-44ce-b2ec-bdae0813b0c6" type="checkbox" ><label for="ee8c16da-5d99-44ce-b2ec-bdae0813b0c6" class="sk-toggleable__label sk-toggleable__label-arrow">HalvingGridSearchCV</label><div class="sk-toggleable__content"><pre>HalvingGridSearchCV(estimator=HistGradientBoostingClassifier(), n_jobs=-1,param_grid={&#x27;max_depth&#x27;: [2, 5, 10],&#x27;max_leaf_nodes&#x27;: [5, 10, 15]},random_state=42)</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="3ab1d862-f650-4be5-9e98-8c2f2f7be60b" type="checkbox" ><label for="3ab1d862-f650-4be5-9e98-8c2f2f7be60b" class="sk-toggleable__label sk-toggleable__label-arrow">HistGradientBoostingClassifier</label><div class="sk-toggleable__content"><pre>HistGradientBoostingClassifier()</pre></div></div></div></div></div></div></div></div></div></div>
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193
  ## Evaluation Results
194
 
 
207
  import joblib
208
  import json
209
  import pandas as pd
210
+ clf = joblib.load(skops-r1ync5kc.pkl)
211
  with open("config.json") as f:
212
  config = json.load(f)
213
  clf.predict(pd.DataFrame.from_dict(config["sklearn"]["example_input"]))
config.json CHANGED
@@ -189,7 +189,7 @@
189
  ]
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  },
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  "model": {
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- "file": "skops-8nefprdu.pkl"
193
  },
194
  "task": "tabular-classification"
195
  }
 
189
  ]
190
  },
191
  "model": {
192
+ "file": "skops-r1ync5kc.pkl"
193
  },
194
  "task": "tabular-classification"
195
  }
init_repo_MLstructureMining.py CHANGED
@@ -63,7 +63,7 @@ model_card.save(Path(local_repo) / "README.md")
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64
  # you can put your own token here, or set it as an environment variable before
65
  # running this script.
66
- token = "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"
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68
  repo_name = f"MLstructureMining"
69
  user_name = HfApi().whoami(token=token)["name"]
 
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64
  # you can put your own token here, or set it as an environment variable before
65
  # running this script.
66
+ token = os.environ["HF_HUB_TOKEN"]
67
 
68
  repo_name = f"MLstructureMining"
69
  user_name = HfApi().whoami(token=token)["name"]
skops-r1ync5kc.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:72d4d5b84193692b34c49716f4b1aaaec5ce423caeab8ad2bd310e037407ed3c
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+ size 242801