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import json
import pandas as pd
import requests
from multiprocessing import Pool
from functools import partial
import streamlit as st
GITHUB_CODE = "https://huggingface.co/datasets/lvwerra/github-code"
INCODER_IMG = (
"https://huggingface.co/datasets/loubnabnl/repo-images/raw/main/incoder.png"
)
@st.cache()
def load_examples():
with open("utils/examples.json", "r") as f:
examples = json.load(f)
return examples
def generate_code(model_name, gen_prompt, max_new_tokens, temperature, seed):
url = (
f"https://hf.space/embed/loubnabnl/{model_name.lower()}-subspace/+/api/predict/"
)
r = requests.post(
url=url, json={"data": [gen_prompt, max_new_tokens, temperature, seed]}
)
generated_text = r.json()["data"][0]
return generated_text
st.set_page_config(page_icon=":laptop:", layout="wide")
st.sidebar.header("Models")
models = ["CodeParrot", "InCoder"]
selected_models = st.sidebar.multiselect(
"Select code generation models to compare", models, default=["CodeParrot"]
)
st.sidebar.header("Tasks")
tasks = [
" ",
"Pretraining datasets",
"Model architecture",
"Model evaluation",
"Code generation",
]
selected_task = st.sidebar.selectbox("Select a task", tasks)
if selected_task == " ":
st.title("Code Generation Models")
with open("utils/intro.txt", "r") as f:
intro = f.read()
st.markdown(intro) |