diff --git a/src/zeroband/models/llama/__init__.py b/src/zeroband/models/llama/__init__.py
index ff142d26..7e55aafb 100644
--- a/src/zeroband/models/llama/__init__.py
+++ b/src/zeroband/models/llama/__init__.py
@@ -7,7 +7,7 @@
 # Llama 2 is licensed under the LLAMA 2 Community License,
 # Copyright (c) Meta Platforms, Inc. All Rights Reserved.
 
-from zeroband.models.llama.model import ModelArgs, Transformer
+from zeroband.models.llama.model import AttnFnType, ModelArgs, Transformer
 
 __all__ = ["Transformer"]
 
@@ -85,7 +85,7 @@ def get_model(
     type_model: str,
     vocab_size: int,
     seq_length: int,
-    math_attn: bool,
+    attn_fn: AttnFnType,
 ) -> tuple[Transformer, ModelArgs]:
     """get the transformer model"""
 
@@ -98,6 +98,6 @@ def get_model(
 
     config.vocab_size = vocab_size
     config.max_seq_len = seq_length
-    config.math_attn = math_attn
+    config.attn_fn = attn_fn
 
     return Transformer(config), config
diff --git a/src/zeroband/models/llama/model.py b/src/zeroband/models/llama/model.py
index c1a63403..cb767790 100644
--- a/src/zeroband/models/llama/model.py
+++ b/src/zeroband/models/llama/model.py
@@ -13,7 +13,7 @@
 
 import contextlib
 from dataclasses import dataclass
-from typing import Optional, Tuple
+from typing import Literal, Optional, Tuple, TypeAlias
 
 import torch
 import torch.nn.functional as F
@@ -41,6 +41,9 @@ def flex_attention_compiled(
     return _flex_attention_compiled(q, k, v, block_mask=block_mask)
 
 
+AttnFnType: TypeAlias = Literal["flex", "math"]
+
+
 @dataclass
 class ModelArgs:
     dim: int = 4096
@@ -60,7 +63,7 @@ class ModelArgs:
     depth_init: bool = True
     norm_type: str = "fused_rmsnorm"
 
-    math_attn: bool = False  # slow for testing
+    attn_fn: AttnFnType = "flex"  # slow for testing
 
 
 def precompute_freqs_cis(dim: int, end: int, theta: float = 10000.0) -> torch.Tensor:
@@ -226,7 +229,7 @@ def __init__(self, model_args: ModelArgs):
         self.wv = nn.Linear(model_args.dim, self.n_kv_heads * self.head_dim, bias=False)
         self.wo = nn.Linear(model_args.n_heads * self.head_dim, model_args.dim, bias=False)
 
-        self.math_attn = model_args.math_attn
+        self.attn_fn = model_args.attn_fn
 
     def init_weights(self, init_std: float):
         for linear in (self.wq, self.wk, self.wv):
@@ -277,7 +280,7 @@ def forward(
         return self.wo(output)
 
     def _sdpa_attention(self, xq, xk, xv) -> torch.Tensor:
-        with sdpa_kernel(SDPBackend.MATH) if self.math_attn else contextlib.nullcontext():
+        with sdpa_kernel(SDPBackend.MATH) if self.attn_fn == "math" else contextlib.nullcontext():
             output = F.scaled_dot_product_attention(xq, xk, xv, is_causal=True)
         output = output.transpose(1, 2).contiguous()  # (bs, seqlen, n_local_heads, head_dim)
         return output
diff --git a/src/zeroband/train.py b/src/zeroband/train.py
index a7f6d486..9f4a5f5c 100644
--- a/src/zeroband/train.py
+++ b/src/zeroband/train.py
@@ -1,7 +1,6 @@
 import os
 from typing import Literal
 import time
-import warnings
 from pydantic import model_validator
 from multiprocessing.process import _children
 
@@ -19,7 +18,7 @@
 from zeroband.diloco import Diloco, DilocoConfig
 from zeroband.comms import ElasticDeviceMesh
 from zeroband.loss import cross_entropy_max_z_loss
-from zeroband.models.llama.model import create_block_mask_from_seqlens
+from zeroband.models.llama.model import AttnFnType, create_block_mask_from_seqlens
 
 from zeroband.utils import (
     FakeTokenizer,
@@ -74,16 +73,8 @@ class TrainConfig(BaseConfig):
     memory_profiler: MemoryProfilerConfig | None = None
 
     sequence_packing: bool = True
-    attn_fn: Literal["flash", "sdpa"] | None = None
 
-    math_attn: bool = False  # slow
-
-    @model_validator(mode="after")
-    def validate_attn_fn(self):
-        if self.attn_fn is not None:
-            warnings.warn("attn_fn argument is deprecated")
-
-        return self
+    attn_fn: AttnFnType = "flex"
 
 
 class MonitorConfig(BaseConfig):
@@ -200,7 +191,7 @@ def train(config: Config):
         config.type_model,
         vocab_size=len(tokenizer) if config.name_model != "debugmodel" or not config.data.fake else TEST_VOCAB_SIZE,
         seq_length=config.data.seq_length,
-        math_attn=config.train.math_attn,
+        attn_fn=config.train.attn_fn,
     )
 
     model = model.to(world_info.local_rank)
diff --git a/tests/test_torchrun/test_train.py b/tests/test_torchrun/test_train.py
index dc36701a..aa04b0c5 100644
--- a/tests/test_torchrun/test_train.py
+++ b/tests/test_torchrun/test_train.py
@@ -144,7 +144,8 @@ def test_ckpt(tmp_path: Path):
             "20",
             "--train.log_model_hash",
             "--no-train.sequence_packing",
-            "--train.math_attn",
+            "--train.attn_fn",
+            "math",
         ],
         diloco=True,
     )
@@ -164,7 +165,8 @@ def test_ckpt(tmp_path: Path):
             "20",
             "--train.log_model_hash",
             "--no-train.sequence_packing",
-            "--train.math_attn",
+            "--train.attn_fn",
+            "math",
         ],
         diloco=True,
     )
@@ -184,7 +186,8 @@ def test_ckpt(tmp_path: Path):
     #         "20",
     #         "--train.log_model_hash",
     #         "--no-train.sequence_packing",
-    #         "--train.math_attn",
+    #         "--train.attn_fn",
+    #         "math",
     #     ],
     #     diloco=True,
     # )