diff --git a/setup.py b/setup.py
index cb8e558c..c1e0d1e4 100644
--- a/setup.py
+++ b/setup.py
@@ -70,6 +70,7 @@ def _setup_entry_points() -> Dict:
     return {
         "console_scripts": [
             "sparsify.auto=sparsify.auto:main",
+            "sparsify.one-shot=sparsify.one_shot:main",
         ]
     }
 
diff --git a/src/sparsify/one_shot.py b/src/sparsify/one_shot.py
new file mode 100644
index 00000000..415614f9
--- /dev/null
+++ b/src/sparsify/one_shot.py
@@ -0,0 +1,110 @@
+# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import argparse
+from pathlib import Path
+
+from sparsify.utils import constants
+
+
+try:
+    from sparsifyml import one_shot
+except ImportError as e:
+    # cheeky lazy define the exception only if we need it rofl
+    class SparsifyLoginRequired(Exception):
+        """You need to run `sparsify.login`"""
+
+    raise SparsifyLoginRequired("Use `sparsify.login` to enable this command.") from e
+
+_SUPPORTED_MODEL_FORMATS = [".onnx"]
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter
+    )
+
+    info = parser.add_argument_group("Project")
+    info.add_argument(
+        "--task",
+        required=True,
+        choices=sorted(constants.TASK_REGISTRY.keys()),
+        help="The task this model is for",
+    )
+    info.add_argument(
+        "--deploy-dir",
+        default=None,
+        type=str,
+        help="Path to save the deployment ready model to",
+    )
+
+    model = parser.add_argument_group("Model")
+    model.add_argument(
+        "--model",
+        required=True,
+        type=str,
+        help=(
+            "Path to model file. "
+            f"The following formats are supported: {_SUPPORTED_MODEL_FORMATS}"
+        ),
+    )
+    model.add_argument(
+        "--recipe", default=None, type=str, help="Recipe to override automatic recipe."
+    )
+
+    data = parser.add_argument_group("Data")
+    data.add_argument(
+        "--dataset", required=True, type=str, help="Path to dataset folder"
+    )
+    data.add_argument(
+        "--num-samples",
+        default=-1,
+        type=int,
+        help=(
+            "Number of samples to use from the dataset for processing. "
+            "-1 means the entire dataset."
+        ),
+    )
+    data.add_argument(
+        "--eval-metric",
+        default="kl",
+        choices=["kl", "accuracy", "mAP", "recall", "f1"],
+        help="Metric that the model is evaluated against on the task.",
+    )
+
+    optim = parser.add_argument_group("Optimization")
+    optim.add_argument(
+        "--opt-level",
+        default="balanced",
+        choices=["balanced", "throughput", "latency", "size", "memory"],
+        help="What to optimize the model for.",
+    )
+
+    args = parser.parse_args()
+
+    one_shot.one_shot(
+        task=args.task,
+        model_file=Path(args.model),
+        dataset_dir=Path(args.dataset),
+        num_samples=args.num_samples,
+        deploy_dir=Path(args.deploy_dir),
+        eval_metric=args.eval_metric,
+        opt_level=args.opt_level,
+        recipe_file=Path(args.recipe) if args.recipe is not None else None,
+    )
+
+
+if __name__ == "__main__":
+    main()