Балаганский Никита Николаевич
commited on
Commit
•
cb4bf13
1
Parent(s):
8a34322
warning about fp16
Browse files
app.py
CHANGED
@@ -131,7 +131,7 @@ def main():
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st.write(WARNING_TEXT[language])
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show_pos_alpha = st.checkbox("Show positive alphas", value=False)
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if act_type == "softmax":
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-
alpha = st.slider("α", min_value=-
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else:
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alpha = st.slider("α", min_value=-5, max_value=5 if show_pos_alpha else 0, step=1, value=0)
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with st.expander("Advanced settings"):
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@@ -155,10 +155,16 @@ def main():
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figure.update_layout(paper_bgcolor="#FFFFFF", plot_bgcolor='#FFFFFF', showlegend=False)
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st.plotly_chart(figure, use_container_width=True)
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st.subheader("What is it?")
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st.write(""
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-
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fp16 = st.checkbox("FP16", value=True)
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st.session_state["generated_text"] = None
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if "sst" in cls_model_name:
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prompt = st.text_input(TEXT_PROMPT_LABEL[language], "The movie")
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st.write(WARNING_TEXT[language])
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show_pos_alpha = st.checkbox("Show positive alphas", value=False)
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if act_type == "softmax":
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+
alpha = st.slider("α", min_value=-30, max_value=30 if show_pos_alpha else 0, step=1, value=0)
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else:
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alpha = st.slider("α", min_value=-5, max_value=5 if show_pos_alpha else 0, step=1, value=0)
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with st.expander("Advanced settings"):
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figure.update_layout(paper_bgcolor="#FFFFFF", plot_bgcolor='#FFFFFF', showlegend=False)
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st.plotly_chart(figure, use_container_width=True)
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st.subheader("What is it?")
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st.write("Text generation with an external classifier requires a huge amount of computation. "
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"Therefore text generating with CAIF could be slow. "
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"To overcome this issue, we can apply reweighting not for every step. "
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"Our hypothesis is that we can run reweighting only "
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"if entropy of the next token is above certain threshold. "
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"This strategy will reduce the amount of computation. "
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"Note that if entropy threshold is too high, we don't get desired attribute in generated text")
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fp16 = st.checkbox("FP16", value=True)
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st.write("FP16 computation is faster in comparison with full precision, "
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"but sometimes could yield Nones (especially with large alphas).")
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st.session_state["generated_text"] = None
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if "sst" in cls_model_name:
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prompt = st.text_input(TEXT_PROMPT_LABEL[language], "The movie")
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