text-generation / app.py
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from fastapi import FastAPI
from transformers import pipeline
description = """
## Text Generation with πŸ€— transformers, FastAPI, and Docker
This app shows how to do text generation with Flan-T5 using FastAPI in a Docker Space πŸš€
Check out the [`/generate`](#/default/generate_generate_get) endpoint below to try it out!
"""
# NOTE - we configure docs_url to serve the interactive Docs at the root path
# of the app. This way, we can use the docs as a landing page for the app on Spaces.
app = FastAPI(docs_url="/", description=description)
pipe = pipeline("text2text-generation", model="google/flan-t5-small")
@app.get("/generate")
def generate(text: str):
"""
Using the text2text-generation pipeline from `transformers`, generate text
from the given input text. The model used is `google/flan-t5-small`, which
can be found [here](https://huggingface.co/google/flan-t5-small).
"""
output = pipe(text)
return {"output": output[0]["generated_text"]}