make sure to handle num-processes with cloud

src/axolotl/cli/cloud/__init__.py

@@ -35,13 +35,14 @@ def do_cli_train(
     cloud_config: Union[Path, str],
     config: Union[Path, str],
     accelerate: bool = True,
+    **kwargs,
 ) -> None:
     print_axolotl_text_art()
     cloud_cfg = load_cloud_cfg(cloud_config)
     cloud = ModalCloud(cloud_cfg)
     with open(config, "r", encoding="utf-8") as file:
         config_yaml = file.read()
-    cloud.train(config_yaml, accelerate=accelerate)
+    cloud.train(config_yaml, accelerate=accelerate, **kwargs)
 
 
 def do_cli_lm_eval(

src/axolotl/cli/cloud/modal_.py

@@ -217,7 +217,7 @@ class ModalCloud(Cloud):
             secrets=self.get_secrets(),
         )
 
-    def train(self, config_yaml: str, accelerate: bool = True):
+    def train(self, config_yaml: str, accelerate: bool = True, **kwargs):
         modal_fn = self.get_train_env()(_train)
         with modal.enable_output():
             with self.app.run(detach=True):
@@ -225,6 +225,7 @@ class ModalCloud(Cloud):
                     config_yaml,
                     accelerate=accelerate,
                     volumes={k: v[0] for k, v in self.volumes.items()},
+                    **kwargs,
                 )
 
     def lm_eval(self, config_yaml: str):
@@ -255,7 +256,7 @@ def _preprocess(config_yaml: str, volumes=None):
     )
 
 
-def _train(config_yaml: str, accelerate: bool = True, volumes=None):
+def _train(config_yaml: str, accelerate: bool = True, volumes=None, **kwargs):
     with open(
         "/workspace/artifacts/axolotl/config.yaml", "w", encoding="utf-8"
     ) as f_out:
@@ -265,8 +266,11 @@ def _train(config_yaml: str, accelerate: bool = True, volumes=None):
         accelerate_args = "--accelerate"
     else:
         accelerate_args = "--no-accelerate"
+    num_processes_args = ""
+    if num_processes := kwargs.pop("num_processes", None):
+        num_processes_args = f"--num-processes {num_processes}"
     run_cmd(
-        f"axolotl train {accelerate_args} /workspace/artifacts/axolotl/config.yaml",
+        f"axolotl train {accelerate_args} {num_processes_args} /workspace/artifacts/axolotl/config.yaml",
         run_folder,
         volumes,
     )

src/axolotl/cli/main.py

@@ -221,7 +221,9 @@ def train(
                     subprocess.run(cmd, check=True)  # nosec B603
             else:
                 if cloud:
-                    do_cli_train(cloud_config=cloud, config=config, accelerate=False)
+                    do_cli_train(
+                        cloud_config=cloud, config=config, accelerate=False, **kwargs
+                    )
                 else:
                     from axolotl.cli.train import do_cli