Saved DRBest model pickle doesn't work at another server

Hi

I got trained DRLearner model here:

dr_best = DRLearner( 
 model_propensity=propensity_best, 
 model_regression=outcome_best, 
 model_final=final_best, 
 categories='auto', 
 discrete_outcome=True, 
 random_state=1, 
 cv=1 ) 

dr_best.fit(Y=Y_full, T=T_fulli, X=X_full)

I got 3 treatments and 1 control group.

After training I saved model with pickle.

At that point, everything is fine.

So whenever I try to load the model on differenet server I got this error:

NotFittedError: Estimator not fitted, call fit before exploiting the model.

After that I try to save models one by one (extracting sklearn wrapper and reach the models) but I couldnt get the same predictions (I use model.effect() in order to get scores).

I asked this situation to ChatGPT and I got this answer:

Because:

LightGBM booster C++ binary
Pickle doesn't guarantee binary compatibility

Therefore, this happens:
"The model was fitted, but it's not considered fitted here"
This is a transport problem, not a training problem.

I also checked the environment library versions of both server, everthing is same. So how can I solve this problem?

Start by reproducing the provided DRLearner training, pickle save, and cross-server load sequence, then compare the reported library environments and the behavior of model.effect(). Done means identifying whether the failure is a supported serialization issue and documenting a reliable way to preserve predictions across servers, or documenting the compatibility limitation.