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Добавлена гистограма.
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app.py
CHANGED
@@ -26,8 +26,7 @@ st.markdown("<p style=\"text-align:center\"><img width=100% src='https://c.tenor
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#st.markdown("#### Title:")
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title = st.text_area("Title:", value="How to cook a neural network", height=16, help="Title of the article")
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abstract = st.text_area("Abstract:",
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value="""
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My dad fits hellish models in general.
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Well, this is about an average recipe, because there are a lot of variations.
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The model is taken, it is not finetuned, finetuning is not about my dad.
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He takes this model, dumps it into the tensorboard and starts frying it.
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@@ -81,11 +80,11 @@ if not text is None and len(text) > 0:
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#st.markdown(f"{keywords}")
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# График важности слов.
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fig, ax = plt.subplots()
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ax.set_title("Ключевые слова в порядке важности")
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bar_width = 0.
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indexes = np.arange(len(labels))
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ax.barh(indexes, scores, bar_width)
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plt.yticks(indexes, labels=labels)
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#st.markdown("#### Title:")
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title = st.text_area("Title:", value="How to cook a neural network", height=16, help="Title of the article")
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abstract = st.text_area("Abstract:",
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+
value="""My dad fits hellish models in general.
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Well, this is about an average recipe, because there are a lot of variations.
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The model is taken, it is not finetuned, finetuning is not about my dad.
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He takes this model, dumps it into the tensorboard and starts frying it.
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#st.markdown(f"{keywords}")
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# График важности слов.
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fig, ax = plt.subplots(figsize=(4, 16))
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ax.set_title("Ключевые слова в порядке важности")
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bar_width = 0.75
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indexes = -np.arange(len(labels))
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ax.barh(indexes, scores, bar_width)
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plt.yticks(indexes, labels=labels)
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