[Python] Sagemaker's SklearnModel requirements.txt not getting installed

This is my code:

from sagemaker.sklearn import SKLearnModel


role = sagemaker.get_execution_role()

model = SKLearnModel(
model_data= f"s3://{default_bucket}/{prefix}/model.tar.gz",
role=role,
entry_point="inference.py",
framework_version="1.2-1",
py_version="py3",
)

predictor = model.deploy(
instance_type="ml.c5.large",
initial_instance_count=1,
container_startup_health_check_timeout=180
)


s3://{default_bucket}/{prefix}/model.tar.gz contains:

Contents of the tarball: (I also tried putting requirements.txt in code/ as advised on documentation for pytorch models on tarball structure)
?rw-r--r-- sagemaker-user/users 4349839 2024-11-29 19:22:21 model.pkl
?rw-r--r-- sagemaker-user/users 24 2024-12-02 14:43:26 inference.py
?rw-r--r-- sagemaker-user/users 44212 2024-11-29 19:23:17 explainer
?rw-r--r-- sagemaker-user/users 24 2024-12-02 14:43:26 requirements.txt


requirements.txt contains:

dill
pandas
joblib


(and I even know pandas is installed by default, checking the aws code)

When I try to deploy I get an error because inference.py has on the first line import dill saying the module is not found and in Cloudwatch I see only inference 1.0.0 is installed (which I assume is my script).

I know I could probably create a subprocess within inference.py and call pip there, but I want to do this properly.

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