make blog

app.py

@@ -33,91 +33,8 @@ def generate_code(model_name, gen_prompt, max_new_tokens, temperature, seed):
 st.set_page_config(page_icon=":laptop:", layout="wide")
 
 # Introduction
-st.title("Code Generation Models")
+st.title("Code generation with 🤗")
 with open("utils/intro.txt", "r") as f:
     intro = f.read()
 st.markdown(intro)
 
-# Pretraining datasets
-st.title("1 - Pretraining datasets 📚")
-st.markdown(
-    f"Preview of some code files from Github repositories in [Github-code dataset]({GITHUB_CODE}):"
-)
-df = pd.read_csv("utils/data_preview.csv")
-st.dataframe(df)
-st.header("Model")
-selected_model = st.selectbox(
-    "Select a code generation model", MODELS, default=["CodeParrot"]
-)
-with open(f"datasets/{selected_model.lower()}.txt", "r") as f:
-    text = f.read()
-st.markdown(text)
-
-# Model architecture
-st.title("Model architecture")
-st.markdow("Most code generation models use GPT style architectures trained on code. Some use encoder-decoder architectures such as AlphaCode.")
-st.header("Model")
-selected_model = st.selectbox(
-    "Select a code generation model", MODELS, default=["CodeParrot"]
-)
-with open(f"architectures/{selected_model.lower()}.txt", "r") as f:
-    text = f.read()
-st.markdown(text)
-if model == "InCoder":
-    st.image(INCODER_IMG, caption="Figure 1: InCoder training", width=700)
-
-# Model evaluation
-st.title("Code models evaluation 📊")
-with open("evaluation/intro.txt", "r") as f:
-    intro = f.read()
-st.markdown(intro)
-
-# Code generation
-st.title("Code generation 💻")
-st.header("Models")
-selected_models = st.sidebar.multiselect(
-    "Select code generation models to compare", MODELS, default=["CodeParrot"]
-)
-st.header("Examples")
-examples = load_examples()
-example_names = [example["name"] for example in examples]
-name2id = dict([(name, i) for i, name in enumerate(example_names)])
-selected_example = st.selectbox(
-    "Select one of the following examples or implement yours", example_names
-)
-example_text = examples[name2id[selected_example]]["value"]
-default_length = examples[name2id[selected_example]]["length"]
-st.header("Generation settings")
-temperature = st.slider(
-    "Temperature:", value=0.2, min_value=0.0, step=0.1, max_value=2.0
-)
-max_new_tokens = st.slider(
-    "Number of tokens to generate:",
-    value=default_length,
-    min_value=8,
-    step=8,
-    max_value=256,
-)
-seed = st.slider(
-    "Random seed:", value=42, min_value=0, step=1, max_value=1000
-)
-gen_prompt = st.text_area(
-    "Generate code with prompt:",
-    value=example_text,
-    height=220,
-).strip()
-if st.button("Generate code!"):
-    with st.spinner("Generating code..."):
-        # Create a multiprocessing Pool
-        pool = Pool()
-        generate_parallel = partial(
-            generate_code,
-            gen_prompt=gen_prompt,
-            max_new_tokens=max_new_tokens,
-            temperature=temperature,
-            seed=seed,
-        )
-        output = pool.map(generate_parallel, selected_models)
-        for i in range(len(output)):
-            st.markdown(f"**{selected_models[i]}**")
-            st.code(output[i])