Model type

1_📝_form.py

@@ -112,6 +112,10 @@ def main():
             "Model_details_text": "",
             "Model_developers": "",
 
+            "Machine_Learning_Type":[],
+            "Modality":[],
+            "Supervision_learning_method":[],
+
             "Model_how_to": "",
             
             "Model_uses": "",
@@ -171,6 +175,8 @@ def main():
 
     warning_placeholder = st.empty()
 
+    Supervision_learning_method_list = ["Unsupervised","Semi-supervised","Self-supervised","Supervised"]
+
     st.text_input("Model Name", key=persist("model_name"))
     st.text_area("Model Description", help="The model description provides basic details about the model. This includes the architecture, version, if it was introduced in a paper, if an original implementation is available, the author, and general information about the model. Any copyright should be attributed here. General information about training procedures, parameters, and important disclaimers can also be mentioned in this section.", key=persist('model_description'))
     st.multiselect("Language(s)", list(languages_map), format_func=lambda x: languages_map[x], help="The language(s) associated with this model. If this is not a text-based model, you should specify whatever lanuage is used in the dataset. For instance, if the dataset's labels are in english, you should select English here.", key=persist("languages"))
@@ -185,6 +191,7 @@ def main():
     st.text_input("Related GitHub Repository", help="Link to a GitHub repository used in the development of this model", key=persist("github_url"))
     st.text_area("Bibtex Citation", help="Bibtex citations for related work", key=persist("bibtex_citations"))
     st.text_input("Carbon Emitted:", help="You can estimate carbon emissions using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700)", key=persist("Model_c02_emitted"))
+    
     # warnings setting
     languages=st.session_state.languages or None
     license=st.session_state.license or None

pages/2_📜_Model_Details.py

@@ -31,38 +31,50 @@ def get_cached_data():
 
 def cs_body():
     license_map= get_cached_data()
+    Supervision_learning_method_list = ["Unsupervised","Semi-supervised","Self-supervised","Supervised"]
+    Machine_Learning_Type_list = ["Neural Network","SVM","Decision Trees","Reinforcement Learning"]
+    Modality_List = ["Computer Vision","Natural Language Processing","Audio","Speech","Multimodal","Tabular"]
+
     #st.set_page_config(layout="wide") ## not yet supported on the hub
     st.markdown('## Model Details')
     st.markdown('### Model Description')
     st.text_area("Provide a 1-2 sentence summary of what this model is.", help="The model description provides basic details about the model. This includes the architecture, version, if it was introduced in a paper, if an original implementation is available, the author, and general information about the model. Any copyright should be attributed here. General information about training procedures, parameters, and important disclaimers can also be mentioned in this section.", key=persist('model_description'))
 
-    left, right = st.columns([2,6])
-
-    with left: 
-        st.write("\n")
-        st.write("\n")
-        st.markdown('### Developed By:')
-        st.write("\n")
-        st.write("\n")
-        #st.write("\n")
-        st.markdown('### Shared By [optional]:')
-        st.write("\n")
-        st.write("\n")
-        st.markdown('### Model Type:')
-        st.write("\n")
-        st.write("\n")
-        st.markdown('### License:')
-    with right:
-        st.write("\n")
-        st.write("\n")
-        st.text_input("",help="Developed By work", key=persist("Model_developers"))
-        st.write("\n")
-        st.write("\n")
-
-        st.text_input("",help="Shared By work",key=persist("shared_by"))
-        st.text_input("",help="Model Type work")
-        #st.write("\n")
-        st.selectbox("",[""] + list(license_map.values()), help="Licenses work", key=persist("license"))
+    left, right = st.columns([4,6])
+    sub_col1, sub_col2, sub_col3 = st.columns(3)
+    with st.container():
+        with left: 
+            st.write("\n")
+            st.write("\n")
+            st.markdown('### Developed By:')
+            st.write("\n")
+            st.write("\n")
+            st.write("\n")
+            st.markdown('### Shared By [optional]:')
+            st.write("\n")
+            st.write("\n")
+            st.write("\n")
+            st.markdown('### License:')
+            st.write("\n")
+            
+            st.markdown('### Model Type:')
+            
+        with right:
+            st.text_input("",help="Developed By work", key=persist("Model_developers"))
+            st.write("\n")
+            st.text_input("",help="Shared By work",key=persist("shared_by"))
+            st.write("\n")
+            st.selectbox("",[""] + list(license_map.values()), help="Licenses work", key=persist("license"))
+        
+    with st.container():
+        
+        with sub_col1:
+            st.multiselect(" Supervision/Learning Method", [""]+ Supervision_learning_method_list, key=persist("Supervision_learning_method"))
+        with sub_col2:
+            st.multiselect("Machine Learning Type",[""]+Machine_Learning_Type_list, key=persist("Machine_Learning_Type"))
+        with sub_col3:
+            st.multiselect("Modality",[""]+Modality_List, key=persist("Modality"))
+        
 
 def main():
     cs_body()