Beginners Guide to Flan-T5

 Flan-T5 is an enhanced version of Google’s T5 AI model which is quite good at certain language tasks.

For example, it’s supposed to be better at a lot of zero-shot examples even than GPT-3.

Install and Setup Flan-T5

First, we install the transformers module by running the below command

pip install transformers

If you run into an issue, check out the Transformers Installation Guide.

Then, we load the Flan-T5 model

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")

Load the tokenizer

tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")

Note we loaded the small model.  You can load any of the versions listed in a later section below.

The bigger the model, the better it is but also more resource consuming

Using Flan-T5 for language AI tasks

Next, we pass the prompt we want the AI model to generate text for.

inputs = tokenizer("A intro paragraph on a article on space travel:", return_tensors="pt")

We call the model’s generate function and get the response.

outputs = model.generate(**inputs)

You can then print the output from the AI model

print(tokenizer.batch_decode(outputs, skip_special_tokens=True))

Flan-T5 versions

Model	Gin File Location	Checkpoint Location
Flan-T5 Small	t5_1_1/small.gin	gs://t5-data/pretrained_models/t5x/flan_t5_small/checkpoint_1198000
Flan-T5 Base	t5_1_1/base.gin	gs://t5-data/pretrained_models/t5x/flan_t5_base/checkpoint_1184000
Flan-T5 Large	t5_1_1_large.gin	gs://t5-data/pretrained_models/t5x/flan_t5_large/checkpoint_1164000
Flan-T5 XL	t5_1_1_xl.gin	gs://t5-data/pretrained_models/t5x/flan_t5_xl/checkpoint_1138000
Flan-T5 XXL	t5_1_1_xxl.gin	gs://t5-data/pretrained_models/t5x/flan_t5_xxl/checkpoint_1114000