Add buck target for hf_download

Differential Revision: D71833608

Pull Request resolved: #9603

Author: jackzhxng

examples/models/llama/TARGETS

@@ -118,6 +118,16 @@ runtime.python_library(
     ],
 )
 
+runtime.python_library(
+    name = "hf_download",
+    srcs = [
+        "hf_download.py",
+    ],
+    deps = [
+        "fbsource//third-party/pypi/huggingface-hub:huggingface-hub",
+    ]
+)
+
 runtime.python_library(
     name = "export_library",
     srcs = [
@@ -134,6 +144,7 @@ runtime.python_library(
         "@EXECUTORCH_CLIENTS",
     ],
     deps = [
+        ":hf_download",
         ":source_transformation",
         "//ai_codesign/gen_ai/fast_hadamard_transform:fast_hadamard_transform",
         "//caffe2:torch",

examples/models/llama/export_llama_lib.py

@@ -539,11 +539,17 @@ def export_llama(args) -> str:
     if not args.checkpoint and args.model in HUGGING_FACE_REPO_IDS:
         repo_id = HUGGING_FACE_REPO_IDS[args.model]
         if args.model == "qwen2_5":
-            from executorch.examples.models.qwen2_5 import convert_weights
+            from executorch.examples.models.qwen2_5 import (  # pyre-ignore[21]
+                convert_weights,
+            )
         elif args.model == "phi_4_mini":
-            from executorch.examples.models.phi_4_mini import convert_weights
+            from executorch.examples.models.phi_4_mini import (  # pyre-ignore[21]
+                convert_weights,
+            )
         elif args.model == "smollm2":
-            from executorch.examples.models.smollm2 import convert_weights
+            from executorch.examples.models.smollm2 import (  # pyre-ignore[21]
+                convert_weights,
+            )
         else:
             raise ValueError(
                 f"Converting weights to meta format for {args.model} is not yet supported"

examples/models/llama/hf_download.py

@@ -36,8 +36,8 @@ def download_and_convert_hf_checkpoint(
     converted_path = cache_dir / f"{model_name}.pth"
 
     if converted_path.exists():
-        print(f"✔ Using cached converted model: {converted_path}")
-        return converted_path
+        print(f"✔ Using cached converted model: {str(converted_path)}")
+        return str(converted_path)
 
     # 1. Download weights from Hugging Face.
     print("⬇ Downloading and converting checkpoint...")
@@ -46,5 +46,5 @@ def download_and_convert_hf_checkpoint(
     )
 
     # 2. Convert weights to Meta format.
-    convert_weights(checkpoint_path, converted_path)
-    return converted_path
+    convert_weights(checkpoint_path, str(converted_path))
+    return str(converted_path)