How to use architecture of T5 without pretrained model (Hugging face)
I would like to study the effect of pre-trained model, so I want to test t5 model with and without pre-trained weights. Using pre-trained weights is straight forward, but I cannot figure out how to use the architecture of T5 from hugging face without the weights. I am using Hugging face with pytorch but open for different solution.

https://huggingface.co/docs/transformers/model_doc/t5#transformers.T5Model
&quot;Initializing with a config file does not load the weights associated with the model, only the configuration.&quot;
for without weights  create a T5Model with config file
from transformers import AutoConfig    
from transformers import T5Tokenizer, T5Model    
model_name = &quot;t5-small&quot;    
config = AutoConfig.from_pretrained(model_name)    
tokenizer = T5Tokenizer.from_pretrained(model_name)    
model = T5Model.from_pretrained(model_name)    
model_raw = T5Model(config)

