Edit :
>T5 - (Text to Text Transfer Transformer) is a large seq2seq transformer model ( it has both encoder and decoder). it is pre-trained on the C4 (Colossal Clean Crawled Corpus) dataset and is flexible for fine-tuning on a variety of downstream tasks. It achieves state-of-the-art results on many NLP benchmarks. T5 models can be used for several NLP tasks such as Summarization, translation, Q&A, text generation etc... for more info on the model refer to this article by Google.
I wanted to share this new library I've been working on and that I open-sourced!.
here are some links to the library:
as the title suggests, you can increase the inference speed of any pretrained T5 model and also decrease the models' size, in a single line of code.
The library can be installed with pip install fastt5. This code snippet from the repository's README gives a concise overview:
The fastT5 library exports the T5 model to onnx with past_key_values, then quantizes it and runs it on onnxruntime.
The exported onnx models support the generate() method of huggingface transformers for inferencing.
for more information on the project refer to the repository here.
The funeral director was asking us what we think Mum should wear in her casket.
Mum always loved to wear sarongs (fabric wraps that go around the torso and drape downward a bit like a long skirt would), so my uncle suggested that she wear a sarong in there.
The funeral director looked a bit confused, as did some of our family members, to which my uncle added:
"What's sarong with that?"
I started laughing like an idiot. He was proud of it too. The funeral director was rather shocked. We assured her, and our more proper relatives, that Mum would've absolutely loved the joke (which is very true).
His delivery was perfect. I'll never forget the risk he took. We sometimes recall the moment as a way help cushion the blows of the grieving process.
--Edit-- I appreciate the condolences. I'm doing well and the worst is behind me and my family. But thanks :)
--Edit-- Massive thanks for all the awards and kind words. And the puns! Love 'em.
I would have a daughter
But Bill kept the Windows
True story; it even happened last night. My 5-year-old son walks up behind me and out of the blue says, "hey."
I turn to him and say, "yeah, kiddo? What's up?"
He responds, "it's dead grass."
I'm really confused and trying to figure out what's wrong and what he wants from me. "What? There's dead grass? What's wrong with that?"
.
.
.
He says, totally straight-faced, "hay is dead grass," and runs off.
You officially hit rock bottom
And then you will all be sorry.
Now it’s syncing.
He replied, "Well, stop going to those places then!"
I will find you. You have my Word.
She said how do you know he was headed to work?
“thank you for your cervix.”
...sails are going through the roof.
Made me smile
Mods said I'm a cereal reposter...
A taxi
But now I stand corrected.
Wait. Sorry, wrong sub.
Wookie mistake.
Theoretical Fizz-ics
Because you can’t ‘C’ in the dark
I said, “That makes two of us.”
so I had to ground him.
He's doing better currently.
And conducting himself properly.
An assassin
Me: Can we change the subject?
My wife: Okay. More chores around the house need to be done by you.
Who buys gummy worms hoping they’d taste as close to real worms as possible?
Crows mostly drank alone.
He's currently assembling his cabinet.
