DrewWalkup
diff --git a/‎llama_cpp/_internals.py
Copy file name to clipboardExpand all lines: llama_cpp/_internals.py
+1-21Lines changed: 1 addition & 21 deletions b/‎llama_cpp/_internals.py
Copy file name to clipboardExpand all lines: llama_cpp/_internals.py
+1-21Lines changed: 1 addition & 21 deletions
diff --git a/‎llama_cpp/llama_cpp.py
Copy file name to clipboardExpand all lines: llama_cpp/llama_cpp.py
-29Lines changed: 0 additions & 29 deletions b/‎llama_cpp/llama_cpp.py
Copy file name to clipboardExpand all lines: llama_cpp/llama_cpp.py
-29Lines changed: 0 additions & 29 deletions
@@ -357,21 +357,6 @@ def sample_repetition_penalties(
             penalty_present,
         )
 
-    def sample_classifier_free_guidance(
-        self,
-        candidates: "_LlamaTokenDataArray",
-        guidance_ctx: "_LlamaContext",
-        scale: float,
-    ):
-        assert self.ctx is not None
-        assert guidance_ctx.ctx is not None
-        llama_cpp.llama_sample_classifier_free_guidance(
-            self.ctx,
-            llama_cpp.byref(candidates.candidates),
-            guidance_ctx.ctx,
-            scale,
-        )
-
     def sample_softmax(self, candidates: "_LlamaTokenDataArray"):
         assert self.ctx is not None
         llama_cpp.llama_sample_softmax(
@@ -720,7 +705,7 @@ def prev_str(self, ctx_main: _LlamaContext, n: int) -> str:
         return ctx_main.model.detokenize(self.prev[-n:]).decode("utf-8")
 
     def sample(
-        self, ctx_main: _LlamaContext, ctx_cfg: Optional[_LlamaContext] = None, idx: int = 0, logits_array: Optional[npt.NDArray[np.single]] = None
+        self, ctx_main: _LlamaContext, idx: int = 0, logits_array: Optional[npt.NDArray[np.single]] = None
     ):
         n_vocab = ctx_main.model.n_vocab()
         id: int = 0
@@ -741,11 +726,6 @@ def sample(
         )  # TODO: Only create this once
         token_data_array.copy_logits(logits_array)
 
-        if ctx_cfg is not None:
-            ctx_main.sample_classifier_free_guidance(
-                token_data_array, ctx_cfg, self.params.cfg_scale
-            )
-
         # apply penalties
         if len(self.prev) > 0:
             nl_token = ctx_main.model.token_nl()
 
@@ -2129,35 +2129,6 @@ def llama_sample_apply_guidance(
     ...
 
 
-# LLAMA_API DEPRECATED(void llama_sample_classifier_free_guidance(
-#           struct llama_context * ctx,
-#         llama_token_data_array * candidates,
-#           struct llama_context * guidance_ctx,
-#                          float   scale),
-#           "use llama_sample_apply_guidance() instead");
-@ctypes_function(
-    "llama_sample_classifier_free_guidance",
-    [
-        llama_context_p_ctypes,
-        llama_token_data_array_p,
-        llama_context_p_ctypes,
-        ctypes.c_float,
-    ],
-    None,
-)
-def llama_sample_classifier_free_guidance(
-    ctx: llama_context_p,
-    candidates: Union[
-        CtypesArray[llama_token_data_array], CtypesPointerOrRef[llama_token_data_array]
-    ],
-    guidance_ctx: llama_context_p,
-    scale: Union[ctypes.c_float, float],
-    /,
-):
-    """Apply classifier-free guidance to the logits as described in academic paper "Stay on topic with Classifier-Free Guidance" https://arxiv.org/abs/2306.17806"""
-    ...
-
-
 # /// @details Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits.
 # LLAMA_API void llama_sample_softmax(
 #         struct llama_context * ctx,