Upload 4 files

README.md

@@ -1,12 +1,13 @@
----
-title: Testwarm
-emoji: 🔥
-colorFrom: purple
-colorTo: blue
-sdk: gradio
-sdk_version: 5.5.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: test warm models
+emoji: 🙄
+colorFrom: indigo
+colorTo: purple
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,60 @@
+import os
+if os.environ.get("SPACES_ZERO_GPU") is not None:
+    import spaces
+else:
+    class spaces:
+        @staticmethod
+        def GPU(func):
+            def wrapper(*args, **kwargs):
+                return func(*args, **kwargs)
+            return wrapper
+import gradio as gr
+import subprocess
+from huggingface_hub import HfApi
+
+@spaces.GPU
+def infer(filter: str, sort: str, sort_dir: bool, infer: str, gated: str, appr: list[str]):
+    try:
+        api = HfApi()
+        kwargs = {}
+        if filter: kwargs["filter"] = filter
+        if gated == "gated": kwargs["gated"] = True
+        elif gated == "non-gated": kwargs["gated"] = False
+        if sort_dir: kwargs["direction"] = -1
+        models = api.list_models(inference=infer, sort=sort, cardData=True, **kwargs)
+        md = "### Results:\n"
+        for model in models:
+            if model.gated and model.gated not in appr: continue
+            md += "1. "
+            md += f"[{model.id}](https://hf.co/{model.id})"
+            md += f" Inference: '{infer}'"
+            #gated_str = model.gated if model.gated else "false"
+            #md += f" Gated: '{gated_str}'"
+            md += f" Gated: '{gated}'"
+            if model.library_name: md += f" Lib:'{model.library_name}'"
+            if model.pipeline_tag: md += f" Pipeline:'{model.pipeline_tag}'"
+            if model.last_modified: md += f" LastMod:'{model.last_modified}'"
+            if model.likes: md += f" Likes:'{model.likes}'"
+            if model.downloads: md += f" DLs:'{model.downloads}'"
+            if model.downloads_all_time: md += f" AllDLs:'{model.downloads_all_time}'"
+            md += "\n"
+        return md
+    except Exception as e:
+        raise gr.Error(e)
+
+with gr.Blocks() as demo:
+    filter = gr.Textbox(label="Query", value="")
+    with gr.Row(equal_height=True):
+        infer_status = gr.Radio(label="Inference status", choices=["warm", "cold", "frozen"], value="warm")
+        gated_status = gr.Radio(label="Gated status", choices=["gated", "non-gated", "all"], value="non-gated")
+        sort = gr.Radio(label="Sort", choices=["last_modified", "likes", "downloads"], value="likes")
+        sort_dir = gr.Checkbox(label="Sort by descending order", value=False)
+        appr_status = gr.CheckboxGroup(label="Approval method", choices=["auto", "manual"], value=["auto", "manual"], visible=False)
+    
+    run_button = gr.Button("Search", variant="primary")
+
+    output_md = gr.Markdown("<br><br>")
+
+    run_button.click(infer, [filter, sort, sort_dir, infer_status, gated_status, appr_status], [output_md])
+
+demo.launch()

pre-requirements.txt

@@ -0,0 +1 @@
+pip>=24.1

requirements.txt

@@ -0,0 +1 @@
+huggingface_hub