let the batch patching begin: parent model+ template updates

1_📝_form.py

@@ -112,6 +112,8 @@ def main():
             "Model_details_text": "",
             "Model_developers": "",
             "blog_url":"",
+            "Parent_Model_url":"",
+            "Parent_Model_name":"",
 
             "Model_how_to": "",
             
@@ -177,6 +179,7 @@ def main():
     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"))
     st.selectbox("License", [""] + list(license_map.values()), help="The license associated with this model.", key=persist("license"))
     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'))
+    st.text_input(" Parent Model (URL)", help="Please provide the URL link to the parent model", key=persist("Parent_Model_name"))
     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"))
     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"))
     st.selectbox("Task", [""] + tasks, help="What task does this model aim to solve?", key=persist('task'))
@@ -186,6 +189,9 @@ 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

language_model_template1.md

@@ -135,12 +135,11 @@
 - **Model type:** {{ model_type | default("Language model", true)}}
 - **Language(s) (NLP):** {{ language | join(', ') | default("More information needed", true)}}
 - **License:** {{ model_license | default("More information needed", true)}}
-- **Related Models:** {{ related_models | join(', ') | default("More information needed", true)}}
-  - **Parent Model:** {{ parent_model | default("More information needed", true)}}
+- **Related Models:** {{ related_models | join(', ') | default("More information needed", true)}} 
+{{ "    -  [Parent Model]({0})".format(repo_link) if parent_model_link }}
 - **Resources for more information:** {{ more_resources | default("More information needed", true)}}
 {{ "    - [GitHub Repo]({0})".format(repo_link) if repo_link }}
 {{ "    - [Associated Paper]({0})".format(paper_link) if paper_link }}
-{{ "    - [Blog Post]({0})".format(blog_link) if blog_link }}
 
 # Uses
 

middleMan.py

@@ -26,6 +26,7 @@ def parse_into_jinja_markdown():
     return (temp.render(model_id = st.session_state["model_name"],
         language = st.session_state["languages"],
         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'],
+        parent_model_link = st.session_state['Parent_Model_url'],
             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"],
             bias_risks_limitations = st.session_state["Model_Limits_n_Risks"], bias_recommendations = st.session_state['Recommendations'],
             model_examination = st.session_state['Model_examin'],

modelcard_template_new_spec.md

@@ -56,8 +56,8 @@
 - **Model type:** Language model
 - **Language(s) (NLP):** {{ language | default("More information needed", true)}}
 - **License:** {{ license | default("More information needed", true)}}
-- **Related Models:** {{ related_models | default("More information needed", true)}}
-  - **Parent Model:** {{ parent_model | default("More information needed", true)}}
+- **Related Models:** {{ related_models | join(', ') | default("More information needed", true)}} 
+{{ "    -  [Parent Model]({0})".format(repo_link) if parent_model_link }}
 - **Resources for more information:** {{ more_resources | default("More information needed", true)}}
 {{ "    - [GitHub Repo]({0})".format(repo_link) if repo_link }}
 {{ "    - [Associated Paper]({0})".format(paper_link) if paper_link }}

pages/2_📜_Model_Details.py

@@ -31,8 +31,8 @@ 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"]
+    Supervision_learning_method_list = ["Unsupervised","Semi-supervised","Self-supervised","Supervised","Reinforcement Learning"]
+    Machine_Learning_Type_list = ["Neural Network","SVM","Decision Trees"]
     Modality_List = ["Computer Vision","Natural Language Processing","Audio","Speech","Multimodal","Tabular"]
 
     #st.set_page_config(layout="wide") ## not yet supported on the hub

template.md

@@ -1,136 +0,0 @@
----
-{{ card_data }}
----
-
-# {{ model_id | default("MyModelName", true)}}
-
-## Table of Contents
-- [{{ model_id | default("MyModelName", true)}}](#-model_id--defaultmymodelname-true)
-  - [Table of Contents](#table-of-contents)
-  - [Model Details](#model-details)
-  - [How to Get Started with the Model](#how-to-get-started-with-the-model)
-  - [Uses](#uses)
-      - [Direct Use](#direct-use)
-      - [Downstream Use](#downstream-use)
-      - [Misuse and Out-of-scope Use](#misuse-and-out-of-scope-use)
-  - [Limitations and Biases](#limitations-and-biases)
-  - [Training](#training)
-      - [Training Data](#training-data)
-      - [Training Procedure](#training-procedure)
-  - [Evaluation Results](#evaluation-results)
-  - [Environmental Impact](#environmental-impact)
-  - [Citation Information](#citation-information)
-
- 
-<model_details>
-## Model Details
-
-<!-- Give an overview of your model, the relevant research paper, who trained it, etc.  -->
-
-{{ model_description if model_description else "[More Information Needed]" }}
-
-- Developed by: {{ authors if authors }}
-- Language(s): {{ languages }}
-- License: This model is licensed under the {{ license }}{{ " license" if "license" not in license.lower() }}
-- Resources for more information:
-{{ "  - [Research Paper](" + paper_url + ")" if paper_url }}
-{{ "  - [GitHub Repo](" + github_url + ")" if github_url }}
-
-</model_details>
-
-<how_to_start>
-## How to Get Started with the Model 
-
-Use the code below to get started with the model.
-
-```python
-# A nice code snippet here that describes how to use the model...
-```
-</how_to_start>
-
-<uses>
-
-## Uses
-
-#### Direct Use
-
-<!-- Describe what kind of tasks this model can be used for directly or problems it can solve. -->
-
-[More Information Needed]
-
-#### Downstream Use
-
-<!-- Describe how this model could be leveraged by a downstream model (if applicable) -->
-
-[More Information Needed]
-
-#### Misuse and Out-of-scope Use
-
-<!-- Describe ways in which this model ***should not*** be used. -->
-
-[More Information Needed]
-</uses>
-
-<Limitations_and_Biases>
-
-## Limitations and Biases
-
-<!-- Describe limitations and biases of this model or models of it's type. -->
-
-**CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propogate historical and current stereotypes.**
-
-[More Information Needed]
-
-</Limitations_and_Biases>
-
-<Training>
-
-## Training
-
-#### Training Data
-
-<!-- Describe the dataset used to train this model. -->
-<!-- Refer to data card if dataset is provided and exists on the hub -->
-
-See the data card for additional information.
-
-#### Training Procedure
-
-<!-- Describe the preprocessing, hardware used, training hyperparameters, etc. -->
-
-[More Information Needed]
-
-</Training>
-
-<Eval_Results>
-## Evaluation Results
-
-<!-- Describe evaluation results of this model across any datasets it was evaluated on. -->
-
-[More Information Needed]
-
-</Eval_Results>
-
-<E_Impact>
-## Environmental Impact
-
-<!-- Provide information to document the environmental impact of this model -->
-
-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)
-
-- **Hardware Type:** 
-- **Hours used:** 
-- **Cloud Provider:** 
-- **Compute Region:** 
-- **Carbon Emitted:** {{ emissions if emissions }}
-
-</E_Impact>
-
-<Cite>
-
-## Citation Information
-
-```bibtex
-{{ bibtex_citations if bibtex_citations }}
-```
-</Cite>