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
from sagemaker.huggingface import HuggingFacePredictor
predictor = HuggingFacePredictor(ENDPOINT_NAME)
response = predictor.predict(payload)
print(response)