Datagran allows you to upload a python Scikit-Learn trained model. Below is an example code:

Dump trained model example:

from sklearn import svm
from sklearn import datasets
clf = svm.SVC()
X, y= datasets.load_iris(return_X_y=True)
clf.fit(X, y)

import pickle
s = pickle.dumps(clf)
open("dump.pkl", "wb").write(s)

Scikit-Learn Pipeline dump:

from sklearn.svm import SVC
from sklearn.preprocessing import StandardScaler
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline
import pickle

X, y = make_classification(random_state=0)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
pipe = Pipeline([('scaler', StandardScaler()), ('svc', SVC())])
pipe.fit(X_train, y_train)
open(
    "pipeline.pkl", "wb"
).write(
    pickle.dumps(pipe)
)

To upload your model just head to your project and in the menu select "Upload Model".