merve HF staff commited on
Commit
0e6d7eb
β€’
1 Parent(s): 5a73471

Update app.py

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Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -19,10 +19,10 @@ def analyze_datasets(dataset, dataset_name, token, column=None, pairwise="off"):
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  analyze_report = sv.analyze(df, target_feat=column, pairwise_analysis=pairwise)
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  else:
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  analyze_report = sv.analyze(df, pairwise_analysis=pairwise)
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- analyze_report.show_html('index.html', open_browser=False)
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  repo_url = create_repo(f"{username}/{dataset_name}", repo_type = "space", token = token, space_sdk = "static", private=False)
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- upload_file(path_or_fileobj ="./index.html", path_in_repo = "./index.html", repo_id =f"{username}/{dataset_name}", repo_type = "space", token=token)
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  readme = f"---\ntitle: {dataset_name}\nemoji: ✨\ncolorFrom: green\ncolorTo: red\nsdk: static\npinned: false\ntags:\n- dataset-report\n---"
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  with open("README.md", "w+") as f:
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  f.write(readme)
@@ -84,7 +84,7 @@ def train_baseline(dataset, dataset_name, token, column):
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  readme+= f"{elem}\n\n"
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  readme+= "\n\n**See model plot below:**\n\n"
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  readme+= re.sub(r"\n\s+", "", str(estimator_html_repr(fc.est_)))
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- readme+= "\n\nThis model is trained with dabl library as a baseline, for better results, use AutoTrain.\n\n"
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  with open(f"{tmpdirname}/README.md", "w+") as f:
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  f.write(readme)
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  with open(f"{tmpdirname}/clf.pkl", mode="bw") as f:
@@ -97,7 +97,7 @@ def train_baseline(dataset, dataset_name, token, column):
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  with gr.Blocks() as demo:
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  main_title = gr.Markdown("""# Baseline Trainer πŸͺ„πŸŒŸβœ¨""")
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- main_desc = gr.Markdown("""This app trains a baseline model for a given dataset and pushes it to your Hugging Face Hub Profile with a model card. For better results, use AutoTrain.""")
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  with gr.Tabs():
 
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  analyze_report = sv.analyze(df, target_feat=column, pairwise_analysis=pairwise)
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  else:
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  analyze_report = sv.analyze(df, pairwise_analysis=pairwise)
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+ analyze_report.show_html('./index.html', open_browser=False)
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  repo_url = create_repo(f"{username}/{dataset_name}", repo_type = "space", token = token, space_sdk = "static", private=False)
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+ upload_file(path_or_fileobj ="./index.html", path_in_repo = "./", repo_id =f"{username}/{dataset_name}", repo_type = "space", token=token)
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  readme = f"---\ntitle: {dataset_name}\nemoji: ✨\ncolorFrom: green\ncolorTo: red\nsdk: static\npinned: false\ntags:\n- dataset-report\n---"
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  with open("README.md", "w+") as f:
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  f.write(readme)
 
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  readme+= f"{elem}\n\n"
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  readme+= "\n\n**See model plot below:**\n\n"
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  readme+= re.sub(r"\n\s+", "", str(estimator_html_repr(fc.est_)))
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+ readme+= "\n\nThis model is trained with dabl library as a baseline, for better results, use [AutoTrain](https://huggingface.co/autotrain).\n\n"
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  with open(f"{tmpdirname}/README.md", "w+") as f:
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  f.write(readme)
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  with open(f"{tmpdirname}/clf.pkl", mode="bw") as f:
 
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  with gr.Blocks() as demo:
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  main_title = gr.Markdown("""# Baseline Trainer πŸͺ„πŸŒŸβœ¨""")
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+ main_desc = gr.Markdown("""This app trains a baseline model for a given dataset and pushes it to your Hugging Face Hub Profile with a model card. For better results, use [AutoTrain](https://huggingface.co/autotrain).""")
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  with gr.Tabs():