Fine-tuning T5 LLM for Text Generation: Complete Tutorial w/ free COLAB #coding

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Real time code to fine tune a T5 LLM model for the downstream task of text summarization. Code to Fine-tune a T5 model.

Your official COLAB Jupyter NB to follow along:
(all rights, credits with corresponding authors of above mentioned NB)

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#machinelearningwithpython
#finetune
#finetuning
#t5

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Fantastic tutorial! It will be great to see one about paraphrasing small articles..

fabsync

Excellent summary. Very nice expressive style. Very impressed.

LuciferHesperus

A comparison video of best services available for fine-tuning? Like Colab Pro, Kaggle, Gradient.

orpvoviv

Thank you for the video! I have a question for you that do you have any tutorial for GENERATIVE question answering by fine tuning BERT or BERTology? Thank you in advance!

TâmVõMinh-tk

Thank you. When I understand correct, it's not possible to train the model via chat (question & answer), right? So no interaction possible?
I learnd that in GPT4ALL with Vicuna or LLAMA 2 with a short story and "dicussion", that nothing was "learned". Looking for information how to do that.

aketo

Really good video. I would appreciate if you can assist me with an answer to a question. From this demo, I see you're using the hugging Face xsum dataset. Can you use a locally available dataset instead? Like a PDF in a local storage
Thanks

damianesene

i am having error in seq2seqTrainingArgument

ajasshaffiajas

To finetune a lanuage model, what kind of data should we feed during the training ?

waeldimassi

Sir please can you guide if i use my custom data which contain 2 seperate file one test and one train so which function i use instead of map ()

iqranaveed

I am trying to fine-tune which is the "GPT-J" model (around 12GiB) in fp16 weights on the Tesla T4 with PEFT - LoRA. I think the GPU isn't enough for this task and it will peak and crash. So, is there any mechanism to avoid crashing? Or only option is to use bigger GPU? And if yes, then which size of GPU would I need?

aayushsmarten

Would love to see a video on paraphrasing.

bharatk

Great video and professional explanation, any idea how to fine tune a question answering problem especially that no prefix exist for such a problem.

TheAIChannel

Awsome video, if we fine tune a model on bf16, and during inference just load the model what's the default D type

riser

Thank you for the video! I have a question about this fine-tuning. Would a t5 model be capable of learning a new task (my use is grammar error correction) I have created a nice dataset with original messy sentence and a correction sentence. It seems to me that it should be able to. Would you prompt it with a new prefix if you want to fine-tune it for this task? Thanks in advance, no worries if you are too busy to answer!

skylerf

Amazing video and well explained. I have a few questions I'd love if you could help me with (I'm a true beginner so sry if I'm asking nonsense):
-Can I fine tune it for the task of translating natural language to query language if I have a dataset for it? (I'd like to say yes since this task falls under machine translation)
- for the evaluation metric, would rouge or blue be better ? Or since it's a query language should I use an exact match metric instead ?
Thanks in advance and keep up with the great content.

zakimihoubi

Awsome video is it better fine tune t5 or flan t5

riser

Is it possible to use 4x RTX 4090 with the 'large' or 'xl' model?

haralc

Can you fine-tune a T5 model for Chatbot like interaction?

beratcimen

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