Hi, @philschmid,
Sorry, you are right, my question was awfully written. Here is the code I used:
!pip install sagemaker --upgrade
from sagemaker.huggingface import HuggingFaceModel
import sagemaker

role = sagemaker.get_execution_role()

# This model was supposedly trained from the dccuchile Bert model for QA.
model = "s3://xxxxxxx/hg_model.tar.gz"
image_uri = "763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:1.7.1-transformers4.6.1-cpu-py36-ubuntu18.04"

huggingface_model = HuggingFaceModel(
    model_data=model,
    transformers_version='4.6.1',
    pytorch_version='1.7.1',
    py_version='py36',
    image_uri=image_uri,
    role=role, 
)

predictor = huggingface_model.deploy(
    initial_instance_count=1,
    instance_type="ml.m5.xlarge"
)

data = {
    "inputs": {
        "question": "¿Cómo me llamo?",
        "context": "Mi nombre es Juan y vivo en Francia"
    }
}

predictor.predict(data)

Reading your comment, I understand that the problem should be on the trained model. I would review the course you recommend and check the training I did.
Thank you!