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| 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." | |
| 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() |