Text AI, Google T5

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


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