Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+
+df = pd.read_csv("https://huggingface.co/datasets/stevhliu/supported-peft-models-methods/raw/main/pefty.csv")
+
+def get_model_and_peft_method(task):
+    """
+    Returns the model and PEFT methods that match a given task.
+    """
+    return df[df['task'] == task].drop('task', axis=1)
+
+demo = gr.Interface(
+    get_model_and_peft_method,
+    inputs=gr.Dropdown(["causal language modeling", "conditional generation", "sequence classification", "token classification", "text-to-image", "image classification", "image-to-text", "semantic segmentation"], label="task"),
+    outputs=gr.Dataframe(headers=["model", "peft method"], label="supported models and PEFT methods"),
+    title="Supported models and PEFT methods",
+    description="Discover what models and PEFT methods are supported for a given task"
+)
+
+demo.launch(debug=True)