update titles
Browse files
app.py
CHANGED
@@ -21,16 +21,16 @@ def load_examples():
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examples = json.load(f)
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return examples
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st.set_page_config(page_icon=
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st.sidebar.header("Models")
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models = ["CodeParrot", "InCoder"]
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selected_models = st.sidebar.multiselect(
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st.sidebar.header("Tasks")
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tasks = [" ", "Pretraining datasets", "Model architecture", "Model evaluation", "Code generation"]
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selected_task = st.sidebar.selectbox("Select a task
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if selected_task == " ":
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@@ -47,7 +47,7 @@ elif selected_task == "Pretraining datasets":
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for model in selected_models:
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with open(f"datasets/{model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(f"### {model}
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st.markdown(text)
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elif selected_task == "Model architecture":
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@@ -55,7 +55,7 @@ elif selected_task == "Model architecture":
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for model in selected_models:
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with open(f"architectures/{model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(f"## {model}
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st.markdown(text)
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elif selected_task == "Model evaluation":
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@@ -70,7 +70,7 @@ elif selected_task == "Code generation":
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examples = load_examples()
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example_names = [example["name"] for example in examples]
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name2id = dict([(name, i) for i, name in enumerate(example_names)])
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selected_example = st.sidebar.selectbox("Select one of the following examples
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example_text = examples[name2id[selected_example]]["value"]
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default_length = examples[name2id[selected_example]]["length"]
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st.sidebar.header("Generation settings")
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@@ -84,5 +84,5 @@ elif selected_task == "Code generation":
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url = f'https://hf.space/embed/loubnabnl/{model.lower()}-subspace/+/api/predict/'
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r = requests.post(url=url, json={"data": [gen_prompt, max_new_tokens, temperature, seed]})
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generated_text = r.json()['data'][0]
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st.markdown(f"{model}
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st.code(generated_text)
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examples = json.load(f)
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return examples
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st.set_page_config(page_icon=":laptop:", layout="wide")
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st.sidebar.header("Models")
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models = ["CodeParrot", "InCoder"]
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selected_models = st.sidebar.multiselect("Select code generation models to compare", models, default=["CodeParrot"])
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st.sidebar.header("Tasks")
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tasks = [" ", "Pretraining datasets", "Model architecture", "Model evaluation", "Code generation"]
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selected_task = st.sidebar.selectbox("Select a task", tasks)
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if selected_task == " ":
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for model in selected_models:
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with open(f"datasets/{model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(f"### {model}")
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st.markdown(text)
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elif selected_task == "Model architecture":
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for model in selected_models:
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with open(f"architectures/{model.lower()}.txt", "r") as f:
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text = f.read()
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st.markdown(f"## {model}")
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st.markdown(text)
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elif selected_task == "Model evaluation":
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examples = load_examples()
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example_names = [example["name"] for example in examples]
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name2id = dict([(name, i) for i, name in enumerate(example_names)])
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selected_example = st.sidebar.selectbox("Select one of the following examples", example_names)
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example_text = examples[name2id[selected_example]]["value"]
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default_length = examples[name2id[selected_example]]["length"]
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st.sidebar.header("Generation settings")
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url = f'https://hf.space/embed/loubnabnl/{model.lower()}-subspace/+/api/predict/'
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r = requests.post(url=url, json={"data": [gen_prompt, max_new_tokens, temperature, seed]})
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generated_text = r.json()['data'][0]
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st.markdown(f"{model}")
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st.code(generated_text)
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