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Modelify takes over all devops jobs from data scientists and machine learning practitioners and brings their models to production.
pip install modelify
Deploying LightGBM Model
import pandas as pd
from sklearn.datasets import load_iris
from lightgbm import LGBMClassifier, Dataset, train as train_lgbm
import modelify
from modelify import ModelInference
from modelify.helpers import create_schema
# import data
iris = load_iris()
df= pd.DataFrame(data= np.c_[iris['data'], iris['target']],
columns= iris['feature_names'] + ['target'])
# train test split
train, test = train_test_split(df, test_size=0.2 )
y_train = df["target"]
X_train = df.drop(columns=["target"])
# build your model
clr = LGBMClassifier()
clr.fit(X_train, y_train)
# deployment
inference = ModelInference(model=model, framework="LIGHTGBM", inputs=create_schema(X_train))
modelify.connect("YOUR_API_KEY")
modelify.deploy(inference, app_uid="YOUR_APP_UID")
FAQs
New Version of MLOps Platforms.
We found that modelify demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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