I created a model resource in sagemaker . the model is a tar file , downloaded from hugging face and fine tuned. based on the documentation provided ( sample code below) . the code sample is passing HF_TASK inference parameter and i assume this is
hugging face specific, but is it possible to pass other parameters like padding or truncation and max_length ? such as
padding : True
truncation: True
max_length = 512 ...
how do i pass these value?
import sagemaker
hub = {
'HF_TASK' : 'text2text-generation'
}
role = sagemaker.get_execution_role()
huggingface_model = HuggingFaceModel( transformers_version='4.6.1', env=hub...
predictor = huggingface_model.deploy( ....
If you are using a Pretrained model you may not be able to tweak params such as padding. I am not sure why do you want to do that while inferencing.