sparsezoo download stub (#360)

* sparsezoo download stub

* lint

src/sparsezoo/download_main.py

@@ -62,8 +62,7 @@ def parse_args():
     parser.add_argument(
         "model_stub",
         type=str,
-        help="Path to a SparseZoo model stub i.e. "
-        "zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/pruned-moderate",
+        help="Path to a SparseZoo model stub i.e. " "zoo:opt-1.3b-opt_pretrain-base",
     )
 
     parser.add_argument(

src/sparsezoo/main.py

@@ -170,7 +170,7 @@
 import argparse
 import logging
 
-from sparsezoo import Model, model_args_to_stub, search_models
+from sparsezoo import Model, search_models
 from sparsezoo.analytics import sparsezoo_analytics
 
 
@@ -281,7 +281,12 @@ def parse_args():
         SEARCH_COMMAND,
         description="Search for objects from the repo.",
     )
-    add_model_arguments(download_parser, download_required=True)
+
+    download_parser.add_argument(
+        "stub",
+        help="Model stub. Please visit sparsezoo.neuralmagic.com to obtain",
+    )
+
     add_model_arguments(search_parser)
 
     download_parser.add_argument(
@@ -373,20 +378,8 @@ def main():
 
     if args.command == DOWNLOAD_COMMAND:
         LOGGER.info("Downloading files from model...")
-        stub = model_args_to_stub(
-            domain=args.domain,
-            sub_domain=args.sub_domain,
-            architecture=args.architecture,
-            sub_architecture=args.sub_architecture,
-            framework=args.framework,
-            repo=args.repo,
-            dataset=args.dataset,
-            training_scheme=args.training_scheme,
-            sparse_name=args.sparse_name,
-            sparse_category=args.sparse_category,
-            sparse_target=args.sparse_target,
-            release_version=args.release_version,
-        )
+
+        stub = args.stub
 
         if args.save_dir:
             model = Model(stub, download_path=args.save_dir)