diff --git a/apps/sft_v2/llama3_8b.yaml b/apps/sft_v2/llama3_8b.yaml
index bd61abe82..86fd88ca5 100644
--- a/apps/sft_v2/llama3_8b.yaml
+++ b/apps/sft_v2/llama3_8b.yaml
@@ -1,9 +1,11 @@
+# >>> python -m apps.sft_v2.main --config apps/sft_v2/llama3_8b.yaml
+
 # Config for supervised full finetuning using a Llama3.1 8B Instruct model
 #
 # This config assumes that you've run the following command before launching
 # this run:
 #   export HF_HUB_DISABLE_XET=1
-#   uv run forge download meta-llama/Meta-Llama-3.1-8B-Instruct
+#   forge download meta-llama/Meta-Llama-3.1-8B-Instruct --output-dir /tmp/Meta-Llama-3.1-8B-Instruct
 
 
 # TODO: required by torchtitan
@@ -14,11 +16,9 @@ comm:
 model:
   name: llama3
   flavor: 8B
-  tokenizer_path: /tmp/Llama-3.1-8B-Instruct
+  hf_assets_path: /tmp/Meta-Llama-3.1-8B-Instruct
 
 processes:
-  scheduler: local # local | mast (not supported yet)
-  hosts: 1
   procs: 8
   with_gpus: true
 
diff --git a/apps/sft_v2/main.py b/apps/sft_v2/main.py
index a2f4f1479..61b27baa3 100644
--- a/apps/sft_v2/main.py
+++ b/apps/sft_v2/main.py
@@ -23,7 +23,7 @@
 
 import torchtitan.experiments.forge.train_spec as forge_train_spec
 from forge.cli.config import parse
-from forge.controller import ForgeActor, spawn_actors
+from forge.controller import ForgeActor
 from forge.data.collate import collate_packed
 from forge.data.datasets.packed import PackedDataset, TextPacker
 from forge.data.datasets.sft_dataset import AlpacaToMessages, sft_iterable_dataset
@@ -130,16 +130,16 @@ async def setup(self):
         # self.logger = self.setup_logger(self.train_config.logger_config)
 
     def setup_data(self):
-        print(os.path.join(self.job_config.model.tokenizer_path, "tokenizer.json"))
+        print(os.path.join(self.job_config.model.hf_assets_path, "tokenizer.json"))
         tokenizer = HuggingFaceModelTokenizer(
             tokenizer_json_path=os.path.join(
-                self.job_config.model.tokenizer_path, "tokenizer.json"
+                self.job_config.model.hf_assets_path, "tokenizer.json"
             ),
             tokenizer_config_json_path=os.path.join(
-                self.job_config.model.tokenizer_path, "tokenizer_config.json"
+                self.job_config.model.hf_assets_path, "tokenizer_config.json"
             ),
             generation_config_path=os.path.join(
-                self.job_config.model.tokenizer_path, "generation_config.json"
+                self.job_config.model.hf_assets_path, "generation_config.json"
             ),
         )
 
@@ -280,22 +280,16 @@ def __repr__(self) -> str:
 async def run(cfg: DictConfig) -> None:
     logging.info("Spawing recipe...")
     process_cfg = cfg.pop("processes")
-    recipe = await spawn_actors(
-        "sft",
-        ForgeSFTRecipe,
-        {"config": cfg},
-        process_cfg,
-        set_address=True,
-    )
+    recipe = await ForgeSFTRecipe.options(**process_cfg).as_actor(cfg)
 
     logging.info("Created recipe, running setup.")
-    await recipe.setup.fanout()
+    await recipe.setup.call()
 
     logging.info("Recipe has been setup. Training now.")
-    await recipe.train.fanout()
+    await recipe.train.call()
 
     logging.info("Done training. Clean up")
-    await recipe.cleanup.fanout()
+    await recipe.cleanup.call()
     await recipe.mesh.stop()
     logging.info("All done!")