huggingface/Model_Cards_Writing_Tool
125
1import streamlit as st2from persist import persist, load_widget_state3from jinja2 import Environment, FileSystemLoader4 5def parse_into_jinja_markdown():6 env = Environment(loader=FileSystemLoader('.'), autoescape=True)7 temp = env.get_template(st.session_state.markdown_upload)8 9 return (temp.render(model_id = st.session_state["model_name"],10 the_model_description = st.session_state["model_description"],developers=st.session_state["Model_developers"],shared_by = st.session_state["shared_by"],model_license = st.session_state['license'],11 direct_use = st.session_state["Direct_Use"], downstream_use = st.session_state["Downstream_Use"],out_of_scope_use = st.session_state["Out-of-Scope_Use"],12 bias_risks_limitations = st.session_state["Model_Limits_n_Risks"], bias_recommendations = st.session_state['Recommendations'],13 model_examination = st.session_state['Model_examin'],14 hardware= st.session_state['Model_hardware'], hours_used = st.session_state['hours_used'], cloud_provider = st.session_state['Model_cloud_provider'], cloud_region = st.session_state['Model_cloud_region'], co2_emitted = st.session_state['Model_c02_emitted'],15 citation_bibtex= st.session_state["APA_citation"], citation_apa = st.session_state['bibtex_citation'],16 training_data = st.session_state['training_data'], preprocessing =st.session_state['preprocessing'], speeds_sizes_times = st.session_state['Speeds_Sizes_Times'],17 model_specs = st.session_state['Model_specs'], compute_infrastructure = st.session_state['compute_infrastructure'],software = st.session_state['technical_specs_software'],18 glossary = st.session_state['Glossary'], 19 more_information = st.session_state['More_info'], 20 model_card_authors = st.session_state['the_authors'],21 model_card_contact = st.session_state['Model_card_contact'],22 get_started_code =st.session_state["Model_how_to"]23 ))24 25def main():26 st.write( parse_into_jinja_markdown())27 28if __name__ == '__main__':29 load_widget_state()30 main()