carbirbal
diff --git a/‎llama_cpp/llama.py
Copy file name to clipboardExpand all lines: llama_cpp/llama.py
+4Lines changed: 4 additions & 0 deletions b/‎llama_cpp/llama.py
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+4Lines changed: 4 additions & 0 deletions
diff --git a/‎llama_cpp/server/settings.py
Copy file name to clipboardExpand all lines: llama_cpp/server/settings.py
+3Lines changed: 3 additions & 0 deletions b/‎llama_cpp/server/settings.py
Copy file name to clipboardExpand all lines: llama_cpp/server/settings.py
+3Lines changed: 3 additions & 0 deletions
@@ -92,6 +92,7 @@ def __init__(
         logits_all: bool = False,
         embedding: bool = False,
         offload_kqv: bool = True,
+        flash_attn: bool = False,
         # Sampling Params
         last_n_tokens_size: int = 64,
         # LoRA Params
@@ -168,6 +169,7 @@ def __init__(
             logits_all: Return logits for all tokens, not just the last token. Must be True for completion to return logprobs.
             embedding: Embedding mode only.
             offload_kqv: Offload K, Q, V to GPU.
+            flash_attn: Use flash attention.
             last_n_tokens_size: Maximum number of tokens to keep in the last_n_tokens deque.
             lora_base: Optional path to base model, useful if using a quantized base model and you want to apply LoRA to an f16 model.
             lora_path: Path to a LoRA file to apply to the model.
@@ -310,6 +312,7 @@ def __init__(
         )  # Must be set to True for speculative decoding
         self.context_params.embeddings = embedding # TODO: Rename to embeddings
         self.context_params.offload_kqv = offload_kqv
+        self.context_params.flash_attn = flash_attn
         #  KV cache quantization
         if type_k is not None:
             self.context_params.type_k = type_k
@@ -1774,6 +1777,7 @@ def __getstate__(self):
             logits_all=self.context_params.logits_all,
             embedding=self.context_params.embeddings,
             offload_kqv=self.context_params.offload_kqv,
+            flash_offload=self.context_params.flash_offload,
             # Sampling Params
             last_n_tokens_size=self.last_n_tokens_size,
             # LoRA Params
 
@@ -96,6 +96,9 @@ class ModelSettings(BaseSettings):
     offload_kqv: bool = Field(
         default=True, description="Whether to offload kqv to the GPU."
     )
+    flash_attn: bool = Field(
+        default=False, description="Whether to use flash attention."
+    )
     # Sampling Params
     last_n_tokens_size: int = Field(
         default=64,