Upload Basic App

app.py

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+from typing import List
+import gradio as gr
+from transformers import AutoModel, AutoTokenizer
+from huggingface_hub import list_models
+
+def get_collection_models(collection_name: str) -> List[str]:
+    """Get a list of models from a specific Hugging Face collection."""
+    models = list_models(author="de-Rodrigo",
+                         filter=f"collections:{collection_name}")
+    model_names = [model.modelId for model in models]
+    return model_names
+
+def load_model(model_name: str):
+    """Load a model from Hugging Face Hub."""
+    model = AutoModel.from_pretrained(model_name)
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    return model, tokenizer
+
+# Example processing function
+def process_input(text: str, model_name: str) -> str:
+    model, tokenizer = load_model(model_name)
+    inputs = tokenizer(text, return_tensors="pt")
+    outputs = model(**inputs)
+    return f"Processed output with {model_name}"
+
+# Create Gradio interface
+def create_interface(collection_name: str):
+    iface = gr.Interface(
+        fn=process_input,
+        inputs=[
+            gr.Textbox(lines=2, placeholder="Enter some text", label="Input Text"),
+            gr.Dropdown(choices=get_collection_models(collection_name), label="Select Model")
+        ],
+        outputs=gr.Textbox(label="Model Output"),
+        title="Hugging Face Model Selector from Collection",
+        description=f"Select a model from the '{collection_name}'.")
+    return iface
+
+# Specify the name of your collection
+collection_name = "VrDU-Doctor"
+iface = create_interface(collection_name)
+iface.launch()

requirements.txt

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+gradio
+transformers
+huggingface_hub=
+torch
+numpy
+Pillo