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import gradio as gr | |
from fastapi import FastAPI | |
from pydantic import BaseModel | |
from transformers import pipeline | |
app = FastAPI() | |
moderate_pipe = pipeline("text-classification", model="KoalaAI/Text-Moderation") | |
class TextInput(BaseModel): | |
text: str | |
async def moderate_text(input: TextInput): | |
results = moderate_pipe(input.text) | |
return {r["label"]: r["score"] for r in results} | |
# Gradio interface to expose the model API via a Space | |
gr.Interface(fn=moderate_text, inputs="text", outputs="json").launch() |