import os
import gradio as gr
import torch
import numpy as np
from transformers import pipeline
import spaces
import torch
pipe_flan = pipeline("text2text-generation", model="philschmid/flan-t5-xxl-sharded-fp16", model_kwargs={"load_in_8bit":True, "device_map": "auto"})
pipe_vanilla = pipeline("text2text-generation", model="t5-large", device="cuda:0", model_kwargs={"torch_dtype":torch.bfloat16})
examples = [
["Please answer to the following question. Who is going to be the next Ballon d'or?"],
["Q: Can Barack Obama have a conversation with George Washington? Give the rationale before answering."],
["Summarize the following text: Peter and Elizabeth took a taxi to attend the night party in the city. While in the party, Elizabeth collapsed and was rushed to the hospital. Since she was diagnosed with a brain injury, the doctor told Peter to stay besides her until she gets well. Therefore, Peter stayed with her at the hospital for 3 days without leaving."],
["Please answer the following question: What is the boiling point of water?"],
["Answer the following question by detailing your reasoning: Are Pokemons alive?"],
["Translate to German: How old are you?"],
["Generate a cooking recipe to make bolognese pasta:"],
["Answer the following yes/no question by reasoning step-by-step. Can you write a whole Haiku in a single tweet?"],
["Premise: At my age you will probably have learnt one lesson. Hypothesis: It's not certain how many lessons you'll learn by your thirties. Does the premise entail the hypothesis?"],
["Answer the following question by reasoning step by step. The cafeteria had 23 apples. If they used 20 for lunch and bought 6 more, how many apples do they have?"],
["""Q: Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?
A: Roger started with 5 balls. 2 cans of 3 tennis balls each is 6 tennis balls. 5 + 6 = 11. The answer is 11.
Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?"""]
]
title = "Flan T5 and Vanilla T5"
description = "This demo compares [T5-large](https://huggingface.co/t5-large) and [Flan-T5-XX-large](https://huggingface.co/google/flan-t5-xxl). Note that T5 expects a very specific format of the prompts, so the examples below are not necessarily the best prompts to compare."
@spaces.GPU
def inference(text):
output_flan = pipe_flan(text, max_length=100)[0]["generated_text"]
output_vanilla = pipe_vanilla(text, max_length=100)[0]["generated_text"]
return [output_flan, output_vanilla]
io = gr.Interface(
inference,
gr.Textbox(lines=3),
outputs=[
gr.Textbox(lines=3, label="Flan T5"),
gr.Textbox(lines=3, label="T5")
],
title=title,
description=description,
examples=examples
)
io.launch()