upload v1673447112 model

app.py

@@ -18,10 +18,10 @@ from huggingface_hub import from_pretrained_keras
 
 PLACEHOLDER_TOKEN="<my-cat-token>"
 
-MODEL_CKPT = "chansung/my-kitty@v1673430532"
+MODEL_CKPT = "chansung/my-kitty@v1673447112"
 MODEL = from_pretrained_keras(MODEL_CKPT)
 
-head_sha = "eaa7a2f3ceaa2e58e7ca10ae2b9337ea6475fa4f"
+head_sha = "119d87285b1a7dda732e72de6028d576af17ef29"
 
 model = keras_cv.models.StableDiffusion(
     img_width=img_width, img_height=img_height, jit_compile=True
@@ -135,6 +135,7 @@ def update_compute_options(provider, region):
     )
 
 def submit(
+    hf_account_input,
     hf_token_input,
     endpoint_name_input,
     provider_selector,
@@ -157,7 +158,7 @@ def submit(
     type = compute_resources[-1].strip()
     
     payload = {
-      "accountId": repository_selector.split("/")[0],
+      "accountId": hf_account_input.strip(),
       "compute": {
         "accelerator": accelerator.lower(),
         "instanceSize": size[1:],
@@ -219,7 +220,13 @@ with gr.Blocks() as hf_endpoint:
     """)
     
     gr.Markdown("""
-    
+    #### Your 🤗 Account ID(Name)
+    """)
+    hf_account_input = gr.Textbox(
+        show_label=False,
+    )
+
+    gr.Markdown("""
     #### Your 🤗 Access Token
     """)
     hf_token_input = gr.Textbox(
@@ -276,7 +283,7 @@ with gr.Blocks() as hf_endpoint:
         )
 
         revision_selector = gr.Textbox(
-            value=f"v1673430532/{head_sha[:7]}",
+            value=f"v1673447112/{head_sha[:7]}",
             interactive=False,
             show_label=False,
         )        
@@ -360,6 +367,7 @@ with gr.Blocks() as hf_endpoint:
     submit_button.click(
         submit, 
         inputs=[
+            hf_account_input,
             hf_token_input,
             endpoint_name_input,
             provider_selector,
@@ -373,6 +381,46 @@ with gr.Blocks() as hf_endpoint:
             security_selector],
         outputs=status_txt)
 
+    gr.Markdown("""    
+    #### Pricing Table(CPU) - 2023/1/11
+    """)
+
+    gr.Dataframe(
+        headers=["provider", "size", "$/h", "vCPUs", "Memory", "Architecture"],
+        datatype=["str", "str", "str", "number", "str", "str"],
+        row_count=8,
+        col_count=(6, "fixed"),
+        value=[
+            ["aws", "small", "$0.06", 1, "2GB", "Intel Xeon - Ice Lake"],
+            ["aws", "medium", "$0.12", 2, "4GB", "Intel Xeon - Ice Lake"],
+            ["aws", "large", "$0.24", 4, "8GB", "Intel Xeon - Ice Lake"],
+            ["aws", "xlarge", "$0.48", 8, "16GB", "Intel Xeon - Ice Lake"],
+            ["azure", "small", "$0.06", 1, "2GB", "Intel Xeon"],
+            ["azure", "medium", "$0.12", 2, "4GB", "Intel Xeon"],
+            ["azure", "large", "$0.24", 4, "8GB", "Intel Xeon"],
+            ["azure", "xlarge", "$0.48", 8, "16GB", "Intel Xeon"],
+        ]
+    )
+
+    gr.Markdown("""    
+    #### Pricing Table(GPU) - 2023/1/11
+    """)    
+
+    gr.Dataframe(
+        headers=["provider", "size", "$/h", "GPUs", "Memory", "Architecture"],
+        datatype=["str", "str", "str", "number", "str", "str"],
+        row_count=6,
+        col_count=(6, "fixed"),
+        value=[
+            ["aws", "small", "$0.60", 1, "14GB", "NVIDIA T4"],
+            ["aws", "medium", "$1.30", 1, "24GB", "NVIDIA A10G"],
+            ["aws", "large", "$4.50", 4, "156B", "NVIDIA T4"],
+            ["aws", "xlarge", "$6.50", 1, "80GB", "NVIDIA A100"],
+            ["aws", "xxlarge", "$7.00", 4, "96GB", "NVIDIA A10G"],
+            ["aws", "xxxlarge", "$45.0", 8, "640GB", "NVIDIA A100"],
+        ]
+    )        
+
 gr.TabbedInterface(
     [demoInterface, hf_endpoint], ["Playground", " Deploy on 🤗 Endpoint"]
 ).launch(enable_queue=True)