diff --git a/src/accelerate/commands/launch.py b/src/accelerate/commands/launch.py
index fd5ad7d60..04ff21127 100644
--- a/src/accelerate/commands/launch.py
+++ b/src/accelerate/commands/launch.py
@@ -343,14 +343,14 @@ def launch_command_parser(subparsers=None):
     )
     deepspeed_args.add_argument(
         "--zero3_init_flag",
-        default=None,
+        default="true",
         type=str,
         help="Decides Whether (true|false) to enable `deepspeed.zero.Init` for constructing massive models. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
     )
     deepspeed_args.add_argument(
         "--zero3_save_16bit_model",
-        default=None,
+        default="false",
         type=str,
         help="Decides Whether (true|false) to save 16-bit model weights when using ZeRO Stage-3. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
@@ -759,15 +759,15 @@ def deepspeed_launcher(args):
     current_env["PYTHONPATH"] = env_var_path_add("PYTHONPATH", os.path.abspath("."))
     current_env["ACCELERATE_MIXED_PRECISION"] = str(mixed_precision)
     current_env["ACCELERATE_USE_DEEPSPEED"] = "true"
-    current_env["DEEPSPEED_ZERO_STAGE"] = str(args.zero_stage)
-    current_env["GRADIENT_ACCUMULATION_STEPS"] = str(args.gradient_accumulation_steps)
-    current_env["GRADIENT_CLIPPING"] = str(args.gradient_clipping).lower()
-    current_env["DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE"] = str(args.offload_optimizer_device).lower()
-    current_env["DEEPSPEED_OFFLOAD_PARAM_DEVICE"] = str(args.offload_param_device).lower()
-    current_env["DEEPSPEED_ZERO3_INIT"] = str(args.zero3_init_flag).lower()
-    current_env["DEEPSPEED_ZERO3_SAVE_16BIT_MODEL"] = str(args.zero3_save_16bit_model).lower()
+    current_env["ACCELERATE_DEEPSPEED_ZERO_STAGE"] = str(args.zero_stage)
+    current_env["ACCELERATE_GRADIENT_ACCUMULATION_STEPS"] = str(args.gradient_accumulation_steps)
+    current_env["ACCELERATE_GRADIENT_CLIPPING"] = str(args.gradient_clipping).lower()
+    current_env["ACCELERATE_DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE"] = str(args.offload_optimizer_device).lower()
+    current_env["ACCELERATE_DEEPSPEED_OFFLOAD_PARAM_DEVICE"] = str(args.offload_param_device).lower()
+    current_env["ACCELERATE_DEEPSPEED_ZERO3_INIT"] = str(args.zero3_init_flag).lower()
+    current_env["ACCELERATE_DEEPSPEED_ZERO3_SAVE_16BIT_MODEL"] = str(args.zero3_save_16bit_model).lower()
     if args.deepspeed_config_file is not None:
-        current_env["DEEPSPEED_CONFIG_FILE"] = str(args.deepspeed_config_file)
+        current_env["ACCELERATE_DEEPSPEED_CONFIG_FILE"] = str(args.deepspeed_config_file)
 
     if args.num_machines > 1 and args.deepspeed_multinode_launcher != DEEPSPEED_MULTINODE_LAUNCHERS[1]:
         with open(".deepspeed_env", "a") as f:
@@ -1041,8 +1041,7 @@ def launch_command(args):
             for name, attr in defaults.__dict__.items():
                 if isinstance(attr, dict):
                     for k in defaults.deepspeed_config:
-                        if getattr(args, k) is None:
-                            setattr(args, k, defaults.deepspeed_config[k])
+                        setattr(args, k, defaults.deepspeed_config[k])
                     for k in defaults.fsdp_config:
                         arg_to_set = k
                         if "fsdp" not in arg_to_set:
diff --git a/src/accelerate/utils/dataclasses.py b/src/accelerate/utils/dataclasses.py
index eafad8a09..eea8c3ab3 100644
--- a/src/accelerate/utils/dataclasses.py
+++ b/src/accelerate/utils/dataclasses.py
@@ -361,7 +361,7 @@ def __post_init__(self):
         from .deepspeed import HfDeepSpeedConfig
 
         if self.hf_ds_config is None:
-            self.hf_ds_config = os.environ.get("DEEPSPEED_CONFIG_FILE", "none")
+            self.hf_ds_config = os.environ.get("ACCELERATE_DEEPSPEED_CONFIG_FILE", "none")
         if (
             isinstance(self.hf_ds_config, dict)
             or (isinstance(self.hf_ds_config, str) and self.hf_ds_config != "none")
@@ -377,24 +377,26 @@ def __post_init__(self):
                 raise ValueError("Please specify the ZeRO optimization config in the DeepSpeed config.")
         else:
             if self.gradient_accumulation_steps is None:
-                self.gradient_accumulation_steps = int(os.environ.get("GRADIENT_ACCUMULATION_STEPS", 1))
+                self.gradient_accumulation_steps = int(os.environ.get("ACCELERATE_GRADIENT_ACCUMULATION_STEPS", 1))
 
             if self.gradient_clipping is None:
-                gradient_clipping = os.environ.get("GRADIENT_CLIPPING", "none")
+                gradient_clipping = os.environ.get("ACCELERATE_GRADIENT_CLIPPING", "none")
                 if gradient_clipping != "none":
                     self.gradient_clipping = float(gradient_clipping)
 
             if self.zero_stage is None:
-                self.zero_stage = int(os.environ.get("DEEPSPEED_ZERO_STAGE", 2))
+                self.zero_stage = int(os.environ.get("ACCELERATE_DEEPSPEED_ZERO_STAGE", 2))
 
             if self.offload_optimizer_device is None:
-                self.offload_optimizer_device = os.environ.get("DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
+                self.offload_optimizer_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
 
             if self.offload_param_device is None:
-                self.offload_param_device = os.environ.get("DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
+                self.offload_param_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
 
             if self.zero3_save_16bit_model is None:
-                self.zero3_save_16bit_model = os.environ.get("DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                self.zero3_save_16bit_model = (
+                    os.environ.get("ACCELERATE_DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                )
 
             config = {
                 "train_batch_size": "auto",
@@ -417,7 +419,7 @@ def __post_init__(self):
         self.deepspeed_config = self.hf_ds_config.config
         self.deepspeed_config["steps_per_print"] = float("inf")  # this will stop deepspeed from logging @ stdout
         if self.zero3_init_flag is None:
-            self.zero3_init_flag = os.environ.get("DEEPSPEED_ZERO3_INIT", "false") == "true"
+            self.zero3_init_flag = os.environ.get("ACCELERATE_DEEPSPEED_ZERO3_INIT", "false") == "true"
         if self.zero3_init_flag and not self.hf_ds_config.is_zero3():
             warnings.warn("DeepSpeed Zero3 Init flag is only applicable for ZeRO Stage 3. Setting it to False.")
             self.zero3_init_flag = False


Review comments: body: this logic needs to be recoded since the default is no longer `None` and thus this code will never run.
diff_hunk: @@ -377,24 +377,26 @@ def __post_init__(self):
                 raise ValueError("Please specify the ZeRO optimization config in the DeepSpeed config.")
         else:
             if self.gradient_accumulation_steps is None:
-                self.gradient_accumulation_steps = int(os.environ.get("GRADIENT_ACCUMULATION_STEPS", 1))
+                self.gradient_accumulation_steps = int(os.environ.get("ACCELERATE_GRADIENT_ACCUMULATION_STEPS", 1))
 
             if self.gradient_clipping is None:
-                gradient_clipping = os.environ.get("GRADIENT_CLIPPING", "none")
+                gradient_clipping = os.environ.get("ACCELERATE_GRADIENT_CLIPPING", "none")
                 if gradient_clipping != "none":
                     self.gradient_clipping = float(gradient_clipping)
 
             if self.zero_stage is None:
-                self.zero_stage = int(os.environ.get("DEEPSPEED_ZERO_STAGE", 2))
+                self.zero_stage = int(os.environ.get("ACCELERATE_DEEPSPEED_ZERO_STAGE", 2))
 
             if self.offload_optimizer_device is None:
-                self.offload_optimizer_device = os.environ.get("DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
+                self.offload_optimizer_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
 
             if self.offload_param_device is None:
-                self.offload_param_device = os.environ.get("DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
+                self.offload_param_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
 
             if self.zero3_save_16bit_model is None:
-                self.zero3_save_16bit_model = os.environ.get("DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                self.zero3_save_16bit_model = (
+                    os.environ.get("ACCELERATE_DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                )
body: this logic needs to be recoded since the default is no longer `None` and thus this code will never run.
diff_hunk: @@ -417,7 +419,7 @@ def __post_init__(self):
         self.deepspeed_config = self.hf_ds_config.config
         self.deepspeed_config["steps_per_print"] = float("inf")  # this will stop deepspeed from logging @ stdout
         if self.zero3_init_flag is None:
-            self.zero3_init_flag = os.environ.get("DEEPSPEED_ZERO3_INIT", "false") == "true"
+            self.zero3_init_flag = os.environ.get("ACCELERATE_DEEPSPEED_ZERO3_INIT", "false") == "true"
body: may be add to `help` that `ACCELERATE_DEEPSPEED_ZERO3_INIT` env var can override it?
diff_hunk: @@ -343,14 +343,14 @@ def launch_command_parser(subparsers=None):
     )
     deepspeed_args.add_argument(
         "--zero3_init_flag",
-        default=None,
+        default="true",
         type=str,
         help="Decides Whether (true|false) to enable `deepspeed.zero.Init` for constructing massive models. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
body: may be add to `help` that `ACCELERATE_DEEPSPEED_ZERO3_SAVE_16BIT_MODEL` env var can override it?
diff_hunk: @@ -343,14 +343,14 @@ def launch_command_parser(subparsers=None):
     )
     deepspeed_args.add_argument(
         "--zero3_init_flag",
-        default=None,
+        default="true",
         type=str,
         help="Decides Whether (true|false) to enable `deepspeed.zero.Init` for constructing massive models. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
     )
     deepspeed_args.add_argument(
         "--zero3_save_16bit_model",
-        default=None,
+        default="false",
         type=str,
         help="Decides Whether (true|false) to save 16-bit model weights when using ZeRO Stage-3. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
body: Hello, `ACCELERATE_DEEPSPEED_ZERO3_INIT` is set using `zero3_init_flag` arg, so I don't think explicit mention is required as it is only used internally.
diff_hunk: @@ -343,14 +343,14 @@ def launch_command_parser(subparsers=None):
     )
     deepspeed_args.add_argument(
         "--zero3_init_flag",
-        default=None,
+        default="true",
         type=str,
         help="Decides Whether (true|false) to enable `deepspeed.zero.Init` for constructing massive models. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
body: Same explanation as above
diff_hunk: @@ -343,14 +343,14 @@ def launch_command_parser(subparsers=None):
     )
     deepspeed_args.add_argument(
         "--zero3_init_flag",
-        default=None,
+        default="true",
         type=str,
         help="Decides Whether (true|false) to enable `deepspeed.zero.Init` for constructing massive models. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
     )
     deepspeed_args.add_argument(
         "--zero3_save_16bit_model",
-        default=None,
+        default="false",
         type=str,
         help="Decides Whether (true|false) to save 16-bit model weights when using ZeRO Stage-3. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
body: ah, understood, thank you!
diff_hunk: @@ -343,14 +343,14 @@ def launch_command_parser(subparsers=None):
     )
     deepspeed_args.add_argument(
         "--zero3_init_flag",
-        default=None,
+        default="true",
         type=str,
         help="Decides Whether (true|false) to enable `deepspeed.zero.Init` for constructing massive models. "
         "Only applicable with DeepSpeed ZeRO Stage-3.",
body: Hello, here dataclass object attributes are still `None` initially if the user hasn't passed them explicitly by directly creating `DeepSpeedPlugin` object. In `__post_init__` call, the env variables which were set via [default] cmd args are used for setting dataclass object attributes.
diff_hunk: @@ -377,24 +377,26 @@ def __post_init__(self):
                 raise ValueError("Please specify the ZeRO optimization config in the DeepSpeed config.")
         else:
             if self.gradient_accumulation_steps is None:
-                self.gradient_accumulation_steps = int(os.environ.get("GRADIENT_ACCUMULATION_STEPS", 1))
+                self.gradient_accumulation_steps = int(os.environ.get("ACCELERATE_GRADIENT_ACCUMULATION_STEPS", 1))
 
             if self.gradient_clipping is None:
-                gradient_clipping = os.environ.get("GRADIENT_CLIPPING", "none")
+                gradient_clipping = os.environ.get("ACCELERATE_GRADIENT_CLIPPING", "none")
                 if gradient_clipping != "none":
                     self.gradient_clipping = float(gradient_clipping)
 
             if self.zero_stage is None:
-                self.zero_stage = int(os.environ.get("DEEPSPEED_ZERO_STAGE", 2))
+                self.zero_stage = int(os.environ.get("ACCELERATE_DEEPSPEED_ZERO_STAGE", 2))
 
             if self.offload_optimizer_device is None:
-                self.offload_optimizer_device = os.environ.get("DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
+                self.offload_optimizer_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
 
             if self.offload_param_device is None:
-                self.offload_param_device = os.environ.get("DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
+                self.offload_param_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
 
             if self.zero3_save_16bit_model is None:
-                self.zero3_save_16bit_model = os.environ.get("DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                self.zero3_save_16bit_model = (
+                    os.environ.get("ACCELERATE_DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                )
body: Same explanation as above
diff_hunk: @@ -417,7 +419,7 @@ def __post_init__(self):
         self.deepspeed_config = self.hf_ds_config.config
         self.deepspeed_config["steps_per_print"] = float("inf")  # this will stop deepspeed from logging @ stdout
         if self.zero3_init_flag is None:
-            self.zero3_init_flag = os.environ.get("DEEPSPEED_ZERO3_INIT", "false") == "true"
+            self.zero3_init_flag = os.environ.get("ACCELERATE_DEEPSPEED_ZERO3_INIT", "false") == "true"
body: my bad then! my apologies for the false alert - thank you for explaining, @pacman100!
diff_hunk: @@ -377,24 +377,26 @@ def __post_init__(self):
                 raise ValueError("Please specify the ZeRO optimization config in the DeepSpeed config.")
         else:
             if self.gradient_accumulation_steps is None:
-                self.gradient_accumulation_steps = int(os.environ.get("GRADIENT_ACCUMULATION_STEPS", 1))
+                self.gradient_accumulation_steps = int(os.environ.get("ACCELERATE_GRADIENT_ACCUMULATION_STEPS", 1))
 
             if self.gradient_clipping is None:
-                gradient_clipping = os.environ.get("GRADIENT_CLIPPING", "none")
+                gradient_clipping = os.environ.get("ACCELERATE_GRADIENT_CLIPPING", "none")
                 if gradient_clipping != "none":
                     self.gradient_clipping = float(gradient_clipping)
 
             if self.zero_stage is None:
-                self.zero_stage = int(os.environ.get("DEEPSPEED_ZERO_STAGE", 2))
+                self.zero_stage = int(os.environ.get("ACCELERATE_DEEPSPEED_ZERO_STAGE", 2))
 
             if self.offload_optimizer_device is None:
-                self.offload_optimizer_device = os.environ.get("DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
+                self.offload_optimizer_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_OPTIMIZER_DEVICE", "none")
 
             if self.offload_param_device is None:
-                self.offload_param_device = os.environ.get("DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
+                self.offload_param_device = os.environ.get("ACCELERATE_DEEPSPEED_OFFLOAD_PARAM_DEVICE", "none")
 
             if self.zero3_save_16bit_model is None:
-                self.zero3_save_16bit_model = os.environ.get("DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                self.zero3_save_16bit_model = (
+                    os.environ.get("ACCELERATE_DEEPSPEED_ZERO3_SAVE_16BIT_MODEL", "false") == "true"
+                )

Discussion: body: _The documentation is not available anymore as the PR was closed or merged._