smart model downloading for mlx exo-explore#16

exo/inference/mlx/sharded_utils.py

@@ -157,7 +157,22 @@ async def snapshot_download_async(*args, **kwargs):
     func = partial(snapshot_download, *args, **kwargs)
     return await asyncio.get_event_loop().run_in_executor(None, func)
 
-async def get_model_path(path_or_hf_repo: str, revision: Optional[str] = None) -> Path:
+model_file_to_layers = {
+    "mlx-community/Meta-Llama-3-70B-Instruct-4bit": {
+        "model-00001-of-00008.safetensors": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
+        "model-00002-of-00008.safetensors": [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20],
+        "model-00003-of-00008.safetensors": [20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31],
+        "model-00004-of-00008.safetensors": [31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42],
+        "model-00005-of-00008.safetensors": [42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53],
+        "model-00006-of-00008.safetensors": [53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64],
+        "model-00007-of-00008.safetensors": [64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75],
+        "model-00008-of-00008.safetensors": [75, 76, 77, 78, 79]
+    }
+}
+
+async def get_model_path(path_or_hf_repo: str, shard: Optional[Shard] = None, revision: Optional[str] = None) -> Path:
+
+
     """
     Ensures the model is available locally. If the path does not exist locally,
     it is downloaded from the Hugging Face Hub.
@@ -171,19 +186,24 @@ async def get_model_path(path_or_hf_repo: str, revision: Optional[str] = None) -
     """
     model_path = Path(path_or_hf_repo)
     if not model_path.exists():
+        safetensors_allow_patterns = ["*.safetensors"] if not shard or path_or_hf_repo not in model_file_to_layers else [
+            name for name, included_layers in model_file_to_layers[path_or_hf_repo].items()
+            if any(layer in range(shard.start_layer, shard.end_layer + 1) for layer in included_layers)
+        ]
+        print(f"{safetensors_allow_patterns=}")
+
         try:
             model_path = Path(
                 await snapshot_download_async(
                     repo_id=path_or_hf_repo,
                     revision=revision,
                     allow_patterns=[
                         "*.json",
-                        "*.safetensors",
                         "*.py",
                         "tokenizer.model",
                         "*.tiktoken",
                         "*.txt",
-                    ],
+                    ] + safetensors_allow_patterns,
                 )
             )
         except RepositoryNotFoundError:
@@ -226,7 +246,7 @@ async def load_shard(
         FileNotFoundError: If config file or safetensors are not found.
         ValueError: If model class or args class are not found.
     """
-    model_path = await get_model_path(path_or_hf_repo)
+    model_path = await get_model_path(path_or_hf_repo, shard=shard)
 
     model = load_model_shard(model_path, shard, lazy, model_config)
     if adapter_path is not None: