adde new tdi peer model

app.py

@@ -11,10 +11,10 @@ from mammal_demo.tcr_task import TcrTask
 
 MAIN_MARKDOWN_TEXT = """
 
-The **[ibm/biomed.omics.bl.sm.ma-ted-458m](https://huggingface.co/models?sort=trending&search=ibm%2Fbiomed.omics.bl)**  model family is a biomedical foundation model and its finetuned variants trained on over 2 billion biological samples across multiple modalities, including proteins, small molecules, and single-cell gene data.  
-Designed for robust performance, it achieves state-of-the-art results over a variety of tasks across the entire drug discovery pipeline and the diverse biomedical domains.  
+The **[ibm/biomed.omics.bl.sm.ma-ted-458m](https://huggingface.co/models?sort=trending&search=ibm%2Fbiomed.omics.bl)**  model family is a biomedical foundation model and its finetuned variants trained on over 2 billion biological samples across multiple modalities, including proteins, small molecules, and single-cell gene data.
+Designed for robust performance, it achieves state-of-the-art results over a variety of tasks across the entire drug discovery pipeline and the diverse biomedical domains.
 
-Based on the [**MAMMAL** - **M**olecular **A**ligned **M**ulti-**M**odal **A**rchitecture and **L**anguage](https://arxiv.org/abs/2410.22367v2), a flexible, multi-domain architecture with an adaptable task prompt syntax.  
+Based on the [**MAMMAL** - **M**olecular **A**ligned **M**ulti-**M**odal **A**rchitecture and **L**anguage](https://arxiv.org/abs/2410.22367v2), a flexible, multi-domain architecture with an adaptable task prompt syntax.
 The syntax allows for dynamic combinations of tokens and scalars, enabling classification, regression, and generation tasks either within a single domain or with cross-domain entities.
 
 This page demonstraits a variety of drug discovery and biomedical tasks for the model family.  Select the task to access the specific demos.
@@ -39,6 +39,11 @@ all_models.register_model(
     model_path="ibm/biomed.omics.bl.sm.ma-ted-458m.dti_bindingdb_pkd",
     task_list=[tdi_task],
 )
+all_models.register_model(
+    model_path="ibm/biomed.omics.bl.sm.ma-ted-458m.dti_bindingdb_pkd_peer",
+    task_list=[tdi_task],
+)
+
 all_models.register_model(
     model_path="ibm/biomed.omics.bl.sm.ma-ted-458m.tcr_epitope_bind",
     task_list=[tcr_task],
@@ -84,8 +89,8 @@ def create_application():
             visible=value is not None,
         )
 
-    with gr.Blocks(theme="Zarkel/IBM_Carbon_Theme") as application:
-        application_main_markdown=gr.Markdown(MAIN_MARKDOWN_TEXT, visible=True)
+    with gr.Blocks(theme="../Zarkel/IBM_Carbon_Theme") as application:
+        gr.Markdown(MAIN_MARKDOWN_TEXT, visible=True)
         task_dropdown = gr.Dropdown(
             choices=["Select task"] + list(all_tasks.keys()),
             label="Mammal Task",
@@ -108,16 +113,6 @@ def create_application():
                 visible=False,
             )
 
-            def echo(value):
-                print(value)
-                return value
-
-            # goto_card_button.click(
-            #     fn=None,
-            #     inputs=model_name_dropdown,
-            #     js=f"(model_name_dropdown) => {{ window.open('https://huggingface.co/{model_name_dropdown}', '_blank') }}",
-            #     )
-
             model_name_dropdown.change(
                 model_change, inputs=[model_name_dropdown], outputs=[goto_card_button]
             )