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Ezi Ozoani
commited on
Commit
β’
22ee960
1
Parent(s):
7ca1ef7
let the batch patching begin: fixing (i) and textual information
Browse files- 1_π_form.py +3 -2
- __pycache__/middleMan.cpython-39.pyc +0 -0
- current_card.md +1 -1
- middleMan.py +1 -1
- pages/11_ π¬_Model_Card_Contact.py +1 -1
- pages/12_π©βπ»_How_To_Get_Started.py +1 -1
- pages/13_π_Model_Card_Authors.py +1 -1
- pages/14_π_Glossary.py +1 -1
- pages/2_π_Model_Details.py +3 -3
- pages/3_ π_Uses.py +4 -4
- pages/4_β οΈ_Limits_and_Risks.py +2 -2
- pages/5_ποΈββοΈ_Model_training.py +2 -2
- pages/6_π¬_Model_Evaluation.py +3 -3
- pages/7_π_Model_Examination.py +1 -1
1_π_form.py
CHANGED
@@ -109,6 +109,7 @@ def main():
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"model_description": "Some cool model...",
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"shared_by": "",
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"the_authors":"",
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"Model_details_text": "",
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"Model_developers": "",
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"blog_url":"",
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@@ -176,10 +177,10 @@ def main():
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st.text_input("Model Name", key=persist("model_name"))
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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'))
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-
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
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st.selectbox("License", [""] + list(license_map.values()), help="The license associated with this model.", key=persist("license"))
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st.selectbox("Library Name", [""] + libraries, help="The name of the library this model came from (Ex. pytorch, timm, spacy, keras, etc.). This is usually automatically detected in model repos, so it is not required.", key=persist('library_name'))
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-
st.text_input("
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st.text_input("Datasets (comma separated)", help="The dataset(s) used to train this model. Use dataset id from https://hf.co/datasets.", key=persist("datasets"))
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st.multiselect("Metrics", available_metrics, help="Metrics used in the training/evaluation of this model. Use metric id from https://hf.co/metrics.", key=persist("metrics"))
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st.selectbox("Task", [""] + tasks, help="What task does this model aim to solve?", key=persist('task'))
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"model_description": "Some cool model...",
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"shared_by": "",
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"the_authors":"",
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+
"Shared_by":"",
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"Model_details_text": "",
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"Model_developers": "",
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"blog_url":"",
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st.text_input("Model Name", key=persist("model_name"))
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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'))
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+
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 language that is used in the dataset. For instance, if the dataset's labels are in english, you should select English here.", key=persist("languages"))
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st.selectbox("License", [""] + list(license_map.values()), help="The license associated with this model.", key=persist("license"))
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st.selectbox("Library Name", [""] + libraries, help="The name of the library this model came from (Ex. pytorch, timm, spacy, keras, etc.). This is usually automatically detected in model repos, so it is not required.", key=persist('library_name'))
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st.text_input("Parent Model (URL)", help="If this model has another model as its base, please provide the URL link to the parent model", key=persist("Parent_Model_name"))
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st.text_input("Datasets (comma separated)", help="The dataset(s) used to train this model. Use dataset id from https://hf.co/datasets.", key=persist("datasets"))
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st.multiselect("Metrics", available_metrics, help="Metrics used in the training/evaluation of this model. Use metric id from https://hf.co/metrics.", key=persist("metrics"))
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st.selectbox("Task", [""] + tasks, help="What task does this model aim to solve?", key=persist('task'))
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__pycache__/middleMan.cpython-39.pyc
CHANGED
Binary files a/__pycache__/middleMan.cpython-39.pyc and b/__pycache__/middleMan.cpython-39.pyc differ
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current_card.md
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@@ -48,7 +48,7 @@
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## Model Description
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-
<!-->
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{{ the_model_description | default("More information needed", true)}}
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- **Developed by:** {{ developers | default("More information needed", true)}}
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## Model Description
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+
<!--> This section provides basic information about what the model is, its current status, and where it came from.. <!-->
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{{ the_model_description | default("More information needed", true)}}
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- **Developed by:** {{ developers | default("More information needed", true)}}
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middleMan.py
CHANGED
@@ -25,7 +25,7 @@ def parse_into_jinja_markdown():
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# citation on form: check box for bibtex or apa: then parse
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return (temp.render(model_id = st.session_state["model_name"],
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language = st.session_state["languages"],
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-
the_model_description = st.session_state["model_description"],developers=st.session_state["Model_developers"],shared_by = st.session_state["
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parent_model_link = st.session_state['Parent_Model_url'],
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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"],
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bias_risks_limitations = st.session_state["Model_Limits_n_Risks"], bias_recommendations = st.session_state['Recommendations'],
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# citation on form: check box for bibtex or apa: then parse
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return (temp.render(model_id = st.session_state["model_name"],
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language = st.session_state["languages"],
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+
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'],
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parent_model_link = st.session_state['Parent_Model_url'],
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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"],
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bias_risks_limitations = st.session_state["Model_Limits_n_Risks"], bias_recommendations = st.session_state['Recommendations'],
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pages/11_ π¬_Model_Card_Contact.py
CHANGED
@@ -14,7 +14,7 @@ def main():
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def cs_body():
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st.markdown('# Model Card Contact')
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st.text_area("
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def cs_body():
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st.markdown('# Model Card Contact')
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st.text_area("How can people who have updates to the Model Card contact the authors?", key=persist("Model_card_contact"), )
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pages/12_π©βπ»_How_To_Get_Started.py
CHANGED
@@ -21,7 +21,7 @@ def cs_body():
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st.markdown('# How to Get Started with the Model')
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st.session_state['Model_how_to'] = text_pass
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st.text_area("
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st.markdown('# How to Get Started with the Model')
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st.session_state['Model_how_to'] = text_pass
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st.text_area("Code snippet to show how to use the model.",height = 300, key=persist("Model_how_to"))
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pages/13_π_Model_Card_Authors.py
CHANGED
@@ -16,7 +16,7 @@ def cs_body():
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#card.save('current_editable.md')
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st.markdown('# Model Card Authors [optional]')
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st.text_area("This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc.",height = 180, key=persist("the_authors"))
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#card.save('current_editable.md')
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st.markdown('# Model Card Authors [optional]')
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st.text_area("This section also provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc.",height = 180, help = "The people who actually constructed the Model Card go here.",key=persist("the_authors"))
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pages/14_π_Glossary.py
CHANGED
@@ -12,7 +12,7 @@ def main():
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def cs_body():
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st.markdown('# Glossary [optional]')
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st.text_area("
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def cs_body():
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st.markdown('# Glossary [optional]')
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st.text_area("Terms used in the model card that need to be clearly defined in order to be accessible across audiences go here.",height = 200, key=persist("Glossary"))
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pages/2_π_Model_Details.py
CHANGED
@@ -60,11 +60,11 @@ def cs_body():
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st.markdown('### Model Type:')
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with right:
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st.text_input("",help="
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st.write("\n")
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st.text_input("",help="
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st.write("\n")
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st.selectbox("",[""] + list(license_map.values()), help="
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with st.container():
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st.markdown('### Model Type:')
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with right:
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st.text_input("",help="List the people who built the model.", key=persist("Model_developers"))
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st.write("\n")
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st.text_input("",help="List the people/organization making the model available online.",key=persist("Shared_by"))
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st.write("\n")
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st.selectbox("",[""] + list(license_map.values()), help="The license associated with this model.", key=persist("license"))
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with st.container():
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pages/3_ π_Uses.py
CHANGED
@@ -10,7 +10,7 @@ def main():
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def cs_body():
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st.markdown('# Uses')
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st.text_area("
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left, right = st.columns([2,4])
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#st.markdown('### Model Description')
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st.markdown('### Out-of-Scope Use:')
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with right:
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st.text_area("",help="
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st.text_area("",help="
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st.text_area("", help="
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def cs_body():
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st.markdown('# Uses')
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st.text_area("This section addresses questions around how the model is intended to be used, discusses the foreseeable users of the model (including those affected by the model), and describes uses that are considered out of scope or misuse of the model.")
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left, right = st.columns([2,4])
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#st.markdown('### Model Description')
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st.markdown('### Out-of-Scope Use:')
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with right:
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st.text_area("",help="How can this model be used, without additional post-processing or further pipeline work?", key=persist("Direct_Use"))
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st.text_area("",help="How can this model be used, when incorporated into another system?",key=persist("Downstream_Use"))
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st.text_area("", help="What tasks will the model not work for?", key=persist("Out-of-Scope_Use"))
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pages/4_β οΈ_Limits_and_Risks.py
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@@ -11,7 +11,7 @@ def main():
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def cs_body():
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st.markdown('# Bias, Risks, and Limitations')
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st.text_area("Use this section to convey both technical and sociotechnical limitations",help="Provide an overview of the possible Limitations and Risks that may be associated with this model", key=persist("Model_Limits_n_Risks"), )
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left, right = st.columns([2,4])
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#st.markdown('### Model Description')
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@@ -25,7 +25,7 @@ def cs_body():
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with right:
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#soutput_jinja = parse_into_jinja_markdown()
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st.text_area("",help="
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#st.write("\n")
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def cs_body():
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st.markdown('# Bias, Risks, and Limitations')
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st.text_area("What are the known or foreseeable issues stemming from this model? Use this section to convey both technical and sociotechnical limitations",help="Provide an overview of the possible Limitations and Risks that may be associated with this model", key=persist("Model_Limits_n_Risks"), )
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left, right = st.columns([2,4])
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#st.markdown('### Model Description')
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with right:
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#soutput_jinja = parse_into_jinja_markdown()
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st.text_area("",help="How can the known or foreseeable issues be addressed?", key=persist("Recommendations"))
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#st.write("\n")
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pages/5_ποΈββοΈ_Model_training.py
CHANGED
@@ -60,7 +60,7 @@ def cs_body():
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with right:
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#soutput_jinja = parse_into_jinja_markdown()
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st.text_area("", key=persist("training_Data"))
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#st.write("\n")
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st.write("\n")
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st.write("\n")
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st.write("\n")
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st.write("\n")
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st.text_area("",
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st.text_area("", help = "This section provides information about throughput, start/end time, checkpoint size if relevant, etc.", key=persist("Speeds_Sizes_Times"))
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with right:
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#soutput_jinja = parse_into_jinja_markdown()
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st.text_area("", help ="Ideally this links to a Dataset Card.", key=persist("training_Data"))
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#st.write("\n")
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st.write("\n")
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st.write("\n")
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st.write("\n")
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st.write("\n")
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st.text_area("",key=persist("model_preprocessing"))
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st.text_area("", help = "This section provides information about throughput, start/end time, checkpoint size if relevant, etc.", key=persist("Speeds_Sizes_Times"))
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pages/6_π¬_Model_Evaluation.py
CHANGED
@@ -51,10 +51,10 @@ def cs_body():
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with right:
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#soutput_jinja = parse_into_jinja_markdown()
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st.text_area("", key=persist("Testing_Data"))
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#st.write("\n")
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st.text_area("",help="
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st.text_area("", help="
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st.text_area("", key=persist("Model_Results"))
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with right:
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#soutput_jinja = parse_into_jinja_markdown()
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st.text_area("", help="Ideally this links to a Dataset Card.",key=persist("Testing_Data"))
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#st.write("\n")
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st.text_area("",help="What are the foreseeable characteristics that will influence how the model behaves? This includes domain and context, as well as population subgroups.",key=persist("Factors"))
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st.text_area("", help="What metrics will be used for evaluation in light of tradeoffs between different errors?", key=persist("Metrics"))
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st.text_area("", key=persist("Model_Results"))
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pages/7_π_Model_Examination.py
CHANGED
@@ -18,7 +18,7 @@ def cs_body():
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#help_text = 'Give an overview of your model, the relevant research paper, who trained it, etc.'
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st.markdown('# Model Examination')
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st.text_area("
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#left, right = st.columns([2,4], gap="small")
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#st.markdown('### Model Description')
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#help_text = 'Give an overview of your model, the relevant research paper, who trained it, etc.'
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st.markdown('# Model Examination')
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st.text_area("Experimental: Where explainability/interpretability work can go.",height = 200, key=persist("Model_examin"), )
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#left, right = st.columns([2,4], gap="small")
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#st.markdown('### Model Description')
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