Spaces:
Running
Running
File size: 3,859 Bytes
822e468 19550e0 8aa7c89 19550e0 f56318b 822e468 19550e0 8aa7c89 822e468 19550e0 f56318b 19550e0 f56318b 19550e0 f56318b 8aa7c89 f56318b 19550e0 f56318b 19550e0 f56318b 19550e0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
import os
import asyncio
from concurrent.futures import ThreadPoolExecutor
import requests
import gradio as gr
MAX_NEW_TOKENS = 128
TOKEN = os.environ.get("API_TOKEN", None)
URLS = [
"https://api-inference.huggingface.co/models/google/flan-ul2",
"https://api-inference.huggingface.co/models/google/flan-t5-xxl",
]
def fetch(session, text, api_url):
model = api_url.split("/")[-1]
response = session.post(api_url, json={"inputs": text, "parameters": {"max_new_tokens": MAX_NEW_TOKENS}})
if response.status_code != 200:
return model, None
return model, response.json()
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 UL2 vs Flan T5 XXL"
description = "This demo compares [Flan-T5-xxl](https://huggingface.co/google/flan-t5-xxl) and [Flan-UL2](https://huggingface.co/google/flan-ul2). Learn more about these models in their model card!"
async def inference(text):
with ThreadPoolExecutor(max_workers=2) as executor:
with requests.Session() as session:
session.headers = {"Authorization": f"Bearer {TOKEN}"}
# Initialize the event loop
loop = asyncio.get_event_loop()
tasks = [
loop.run_in_executor(
executor, fetch, *(session, text, url) # Allows us to pass in multiple arguments to `fetch`
)
for url in URLS
]
# Initializes the tasks to run and awaits their results
responses = [None, None]
for (model, response) in await asyncio.gather(*tasks):
if response is not None:
if model == "flan-ul2":
responses[0] = response[0]["generated_text"]
elif model == "flan-t5-xxl":
responses[1] = response[0]["generated_text"]
return responses
io = gr.Interface(
inference,
gr.Textbox(lines=3),
outputs=[gr.Textbox(lines=3, label="Flan T5-UL2"), gr.Textbox(lines=3, label="Flan T5-XXL")],
title=title,
description=description,
examples=examples,
)
io.launch()
|