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Update app.py
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app.py
CHANGED
@@ -5,10 +5,10 @@ import requests.exceptions
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from huggingface_hub import HfApi, hf_hub_download
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from huggingface_hub.repocard import metadata_load
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pipe = joblib.load("https://huggingface.co/spaces/scikit-learn/sentiment-analysis/tree/main/pipeline.pkl")
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inputs = [gr.Textbox(value = "The customer service was satisfactory.")]
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outputs = [gr.Label(label = "Sentiment")]
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title = "Sentiment Analysis"
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app = gr.Blocks()
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def load_agent(model_id_1, model_id_2):
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@@ -77,8 +77,8 @@ with app:
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app_button.click(load_agent, inputs=[model1_input, model2_input], outputs=[model1_name, model1_score_output, model2_name, model2_score_output])
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examples = gr.Examples(examples=[["
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["
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inputs=[model1_input, model2_input])
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from huggingface_hub import HfApi, hf_hub_download
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from huggingface_hub.repocard import metadata_load
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#pipe = joblib.load("https://huggingface.co/spaces/scikit-learn/sentiment-analysis/tree/main/pipeline.pkl")
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#inputs = [gr.Textbox(value = "The customer service was satisfactory.")]
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#outputs = [gr.Label(label = "Sentiment")]
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#title = "Sentiment Analysis"
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app = gr.Blocks()
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def load_agent(model_id_1, model_id_2):
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app_button.click(load_agent, inputs=[model1_input, model2_input], outputs=[model1_name, model1_score_output, model2_name, model2_score_output])
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examples = gr.Examples(examples=[["distilbert-base-uncased-finetuned-sst-2-english","distilbert-base-uncased-finetuned-sst-2-english"],
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["distilbert-base-uncased-finetuned-sst-2-english", "distilbert-base-uncased-finetuned-sst-2-english"]],
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inputs=[model1_input, model2_input])
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