Hello @pavel-nesterov,
Welcome to the Community .
First of all, I saw in Code#1 that you deployed 'distilbert-base-uncased' with question-answering, which is definitely not recommended since it is not fine-tuned for question answering.
The Error:
2021-09-15 06:41:14,481 [INFO ] W-distilbert-base-uncased-1-stdout com.amazonaws.ml.mms.wlm.WorkerLifeCycle - AttributeError: 'numpy.ndarray' object has no attribute 'pop'

raises because you are forcing ContentType='text/csv' for a JSON input, that’s not going to work.
Change ContentType in code#2 to application/json and it should work. Additionally instead of using boto3 + with runtime.sagemaker you could use the sagemaker sdk which provides a HuggingFacePredictor to invoke your endpoints.Hugging Face — sagemaker 2.59.1.post0 documentation 1
from sagemaker.huggingface import HuggingFacePredictor

predictor = HuggingFacePredictor(ENDPOINT_NAME)
response = predictor.predict(payload)
print(response)