update
Browse files
app.py
CHANGED
@@ -30,7 +30,7 @@ def generate_code(model_name, gen_prompt, max_new_tokens, temperature, seed):
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return generated_text
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st.set_page_config(page_icon=":laptop:", layout="wide")
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# Introduction
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st.title("Code generation with π€")
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@@ -46,10 +46,10 @@ st.markdown(
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df = pd.read_csv("utils/data_preview.csv")
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st.dataframe(df)
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st.header("Model")
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-
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"Select a code generation model", MODELS, key=1
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)
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with open(f"datasets/{
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text = f.read()
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st.markdown(text)
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@@ -57,13 +57,13 @@ st.markdown(text)
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st.title("2 - Model architecture")
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st.markdown("Most code generation models use GPT style architectures trained on code. Some use encoder-decoder architectures such as AlphaCode.")
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st.header("Model")
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-
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"Select a code generation model", MODELS, key=2
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)
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with open(f"architectures/{
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text = f.read()
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st.markdown(text)
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if
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st.image(INCODER_IMG, caption="Figure 1: InCoder training", width=700)
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# Model evaluation
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@@ -75,7 +75,7 @@ st.markdown(intro)
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# Code generation
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st.title("4 - Code generation π»")
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st.header("Models")
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-
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"Select code generation models to compare", MODELS, default=["CodeParrot"], key=3
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)
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st.header("Examples")
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@@ -117,7 +117,7 @@ if st.button("Generate code!"):
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temperature=temperature,
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seed=seed,
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)
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output = pool.map(generate_parallel,
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for i in range(len(output)):
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st.markdown(f"**{
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st.code(output[i])
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return generated_text
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+
#st.set_page_config(page_icon=":laptop:", layout="wide")
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# Introduction
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st.title("Code generation with π€")
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df = pd.read_csv("utils/data_preview.csv")
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st.dataframe(df)
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st.header("Model")
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selected_model = st.selectbox(
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"Select a code generation model", MODELS, key=1
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)
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with open(f"datasets/{selected_model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(text)
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st.title("2 - Model architecture")
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st.markdown("Most code generation models use GPT style architectures trained on code. Some use encoder-decoder architectures such as AlphaCode.")
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st.header("Model")
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selected_model = st.selectbox(
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"Select a code generation model", MODELS, key=2
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)
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with open(f"architectures/{selected_model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(text)
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if selected_model == "InCoder":
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st.image(INCODER_IMG, caption="Figure 1: InCoder training", width=700)
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# Model evaluation
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# Code generation
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st.title("4 - Code generation π»")
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st.header("Models")
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selected_models = st.multiselect(
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"Select code generation models to compare", MODELS, default=["CodeParrot"], key=3
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)
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st.header("Examples")
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temperature=temperature,
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seed=seed,
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)
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output = pool.map(generate_parallel, selected_models)
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for i in range(len(output)):
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st.markdown(f"**{selected_models[i]}**")
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st.code(output[i])
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