feat: Update llama.cpp
This commit is contained in:
Andrei Betlen
parent
c07db99e5b
commit
c9b85bf098
2 changed files with 69 additions and 85 deletions
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@ -552,19 +552,25 @@ class llama_batch(ctypes.Structure):
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# LLAMA_KV_OVERRIDE_TYPE_INT,
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# LLAMA_KV_OVERRIDE_TYPE_FLOAT,
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# LLAMA_KV_OVERRIDE_TYPE_BOOL,
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# LLAMA_KV_OVERRIDE_TYPE_STR,
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# };
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LLAMA_KV_OVERRIDE_TYPE_INT = 0
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LLAMA_KV_OVERRIDE_TYPE_FLOAT = 1
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LLAMA_KV_OVERRIDE_TYPE_BOOL = 2
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LLAMA_KV_OVERRIDE_TYPE_STR = 3
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# struct llama_model_kv_override {
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# char key[128];
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# enum llama_model_kv_override_type tag;
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# char key[128];
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# union {
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# int64_t int_value;
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# double float_value;
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# bool bool_value;
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# int64_t val_i64;
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# double val_f64;
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# bool val_bool;
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# char val_str[128];
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# };
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# };
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class llama_model_kv_override_value(ctypes.Union):
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@ -572,16 +578,28 @@ class llama_model_kv_override_value(ctypes.Union):
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("int_value", ctypes.c_int64),
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("float_value", ctypes.c_double),
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("bool_value", ctypes.c_bool),
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("str_value", ctypes.c_char * 128),
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]
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if TYPE_CHECKING:
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int_value: int
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float_value: float
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bool_value: bool
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str_value: bytes
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class llama_model_kv_override(ctypes.Structure):
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_fields_ = [
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("key", ctypes.c_char * 128),
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("tag", ctypes.c_int),
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("key", ctypes.c_char * 128),
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("value", llama_model_kv_override_value),
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]
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if TYPE_CHECKING:
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tag: int
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key: bytes
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value: Union[int, float, bool, bytes]
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# struct llama_model_params {
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# int32_t n_gpu_layers; // number of layers to store in VRAM
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@ -612,6 +630,7 @@ class llama_model_kv_override(ctypes.Structure):
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# bool vocab_only; // only load the vocabulary, no weights
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# bool use_mmap; // use mmap if possible
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# bool use_mlock; // force system to keep model in RAM
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# bool check_tensors; // validate model tensor data
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# };
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class llama_model_params(ctypes.Structure):
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"""Parameters for llama_model
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@ -626,7 +645,8 @@ class llama_model_params(ctypes.Structure):
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kv_overrides (ctypes.Array[llama_model_kv_override]): override key-value pairs of the model meta data
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vocab_only (bool): only load the vocabulary, no weights
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use_mmap (bool): use mmap if possible
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use_mlock (bool): force system to keep model in RAM"""
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use_mlock (bool): force system to keep model in RAM
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check_tensors (bool): validate model tensor data"""
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if TYPE_CHECKING:
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n_gpu_layers: int
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@ -639,6 +659,7 @@ class llama_model_params(ctypes.Structure):
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vocab_only: bool
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use_mmap: bool
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use_mlock: bool
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check_tensors: bool
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_fields_ = [
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("n_gpu_layers", ctypes.c_int32),
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@ -651,6 +672,7 @@ class llama_model_params(ctypes.Structure):
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("vocab_only", ctypes.c_bool),
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("use_mmap", ctypes.c_bool),
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("use_mlock", ctypes.c_bool),
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("check_tensors", ctypes.c_bool),
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]
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@ -1041,8 +1063,7 @@ GGML_NUMA_STRATEGY_COUNT = 5
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[ctypes.c_int],
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None,
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)
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def llama_numa_init(numa: int, /):
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...
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def llama_numa_init(numa: int, /): ...
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# // Call once at the end of the program - currently only used for MPI
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@ -1067,8 +1088,7 @@ def llama_backend_free():
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)
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def llama_load_model_from_file(
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path_model: bytes, params: llama_model_params, /
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) -> Optional[llama_model_p]:
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...
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) -> Optional[llama_model_p]: ...
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# LLAMA_API void llama_free_model(struct llama_model * model);
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@ -1077,8 +1097,7 @@ def llama_load_model_from_file(
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[llama_model_p_ctypes],
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None,
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)
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def llama_free_model(model: llama_model_p, /):
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...
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def llama_free_model(model: llama_model_p, /): ...
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# LLAMA_API struct llama_context * llama_new_context_with_model(
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@ -1091,8 +1110,7 @@ def llama_free_model(model: llama_model_p, /):
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)
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def llama_new_context_with_model(
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model: llama_model_p, params: llama_context_params, /
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) -> Optional[llama_context_p]:
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...
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) -> Optional[llama_context_p]: ...
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# // Frees all allocated memory
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@ -1113,104 +1131,87 @@ def llama_free(ctx: llama_context_p, /):
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[],
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ctypes.c_int64,
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)
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def llama_time_us() -> int:
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...
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def llama_time_us() -> int: ...
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# LLAMA_API size_t llama_max_devices(void);
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@ctypes_function("llama_max_devices", [], ctypes.c_size_t)
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def llama_max_devices() -> int:
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...
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def llama_max_devices() -> int: ...
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# LLAMA_API bool llama_supports_mmap (void);
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@ctypes_function("llama_supports_mmap", [], ctypes.c_bool)
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def llama_supports_mmap() -> bool:
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...
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def llama_supports_mmap() -> bool: ...
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# LLAMA_API bool llama_supports_mlock (void);
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@ctypes_function("llama_supports_mlock", [], ctypes.c_bool)
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def llama_supports_mlock() -> bool:
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...
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def llama_supports_mlock() -> bool: ...
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# LLAMA_API bool llama_supports_gpu_offload(void);
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@ctypes_function("llama_supports_gpu_offload", [], ctypes.c_bool)
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def llama_supports_gpu_offload() -> bool:
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...
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def llama_supports_gpu_offload() -> bool: ...
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# LLAMA_API const struct llama_model * llama_get_model(const struct llama_context * ctx);
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@ctypes_function("llama_get_model", [llama_context_p_ctypes], llama_model_p_ctypes)
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def llama_get_model(ctx: llama_context_p, /) -> Optional[llama_model_p]:
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...
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def llama_get_model(ctx: llama_context_p, /) -> Optional[llama_model_p]: ...
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# LLAMA_API uint32_t llama_n_ctx (const struct llama_context * ctx);
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@ctypes_function("llama_n_ctx", [llama_context_p_ctypes], ctypes.c_uint32)
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def llama_n_ctx(ctx: llama_context_p, /) -> int:
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...
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def llama_n_ctx(ctx: llama_context_p, /) -> int: ...
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# LLAMA_API uint32_t llama_n_batch (const struct llama_context * ctx);
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@ctypes_function("llama_n_batch", [llama_context_p_ctypes], ctypes.c_uint32)
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def llama_n_batch(ctx: llama_context_p, /) -> int:
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...
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def llama_n_batch(ctx: llama_context_p, /) -> int: ...
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# LLAMA_API uint32_t llama_n_ubatch (const struct llama_context * ctx);
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@ctypes_function("llama_n_ubatch", [llama_context_p_ctypes], ctypes.c_uint32)
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def llama_n_ubatch(ctx: llama_context_p, /) -> int:
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...
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def llama_n_ubatch(ctx: llama_context_p, /) -> int: ...
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# LLAMA_API uint32_t llama_n_seq_max (const struct llama_context * ctx);
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@ctypes_function("llama_n_seq_max", [llama_context_p_ctypes], ctypes.c_uint32)
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def llama_n_seq_max(ctx: llama_context_p, /) -> int:
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...
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def llama_n_seq_max(ctx: llama_context_p, /) -> int: ...
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# LLAMA_API enum llama_pooling_type llama_pooling_type(const struct llama_context * ctx);
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@ctypes_function("llama_pooling_type", [llama_context_p_ctypes], ctypes.c_int)
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def llama_pooling_type(ctx: llama_context_p, /) -> int:
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...
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def llama_pooling_type(ctx: llama_context_p, /) -> int: ...
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# LLAMA_API enum llama_vocab_type llama_vocab_type (const struct llama_model * model);
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@ctypes_function("llama_vocab_type", [llama_model_p_ctypes], ctypes.c_int)
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def llama_vocab_type(model: llama_model_p, /) -> int:
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...
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def llama_vocab_type(model: llama_model_p, /) -> int: ...
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# LLAMA_API enum llama_rope_type llama_rope_type (const struct llama_model * model);
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@ctypes_function("llama_rope_type", [llama_model_p_ctypes], ctypes.c_int)
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def llama_rope_type(model: llama_model_p, /) -> int:
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...
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def llama_rope_type(model: llama_model_p, /) -> int: ...
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# LLAMA_API int32_t llama_n_vocab (const struct llama_model * model);
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@ctypes_function("llama_n_vocab", [llama_model_p_ctypes], ctypes.c_int32)
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def llama_n_vocab(model: llama_model_p, /) -> int:
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...
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def llama_n_vocab(model: llama_model_p, /) -> int: ...
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# LLAMA_API int32_t llama_n_ctx_train(const struct llama_model * model);
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@ctypes_function("llama_n_ctx_train", [llama_model_p_ctypes], ctypes.c_int32)
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def llama_n_ctx_train(model: llama_model_p, /) -> int:
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...
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def llama_n_ctx_train(model: llama_model_p, /) -> int: ...
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# LLAMA_API int32_t llama_n_embd (const struct llama_model * model);
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@ctypes_function("llama_n_embd", [llama_model_p_ctypes], ctypes.c_int32)
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def llama_n_embd(model: llama_model_p, /) -> int:
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...
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def llama_n_embd(model: llama_model_p, /) -> int: ...
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# LLAMA_API int32_t llama_n_layer (const struct llama_model * model);
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@ctypes_function("llama_n_layer", [llama_model_p_ctypes], ctypes.c_int32)
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def llama_n_layer(model: llama_model_p, /) -> int:
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...
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def llama_n_layer(model: llama_model_p, /) -> int: ...
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# // Get the model's RoPE frequency scaling factor
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@ -1912,8 +1913,7 @@ def llama_state_load_file(
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n_token_capacity: Union[ctypes.c_size_t, int],
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n_token_count_out: CtypesPointerOrRef[ctypes.c_size_t],
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/,
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) -> bool:
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...
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) -> bool: ...
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# LLAMA_API DEPRECATED(bool llama_load_session_file(
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@ -1941,8 +1941,7 @@ def llama_load_session_file(
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n_token_capacity: Union[ctypes.c_size_t, int],
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n_token_count_out: CtypesPointerOrRef[ctypes.c_size_t],
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/,
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) -> int:
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...
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) -> int: ...
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# LLAMA_API bool llama_state_save_file(
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@ -1966,8 +1965,7 @@ def llama_state_save_file(
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tokens: CtypesArray[llama_token],
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n_token_count: Union[ctypes.c_size_t, int],
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/,
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) -> bool:
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...
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) -> bool: ...
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# LLAMA_API DEPRECATED(bool llama_save_session_file(
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@ -1992,8 +1990,7 @@ def llama_save_session_file(
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tokens: CtypesArray[llama_token],
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n_token_count: Union[ctypes.c_size_t, int],
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/,
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) -> int:
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...
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) -> int: ...
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# // Get the exact size needed to copy the KV cache of a single sequence
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@ -2071,8 +2068,7 @@ def llama_state_seq_save_file(
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tokens: CtypesArray[llama_token],
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n_token_count: Union[ctypes.c_size_t, int],
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/,
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) -> int:
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...
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) -> int: ...
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# LLAMA_API size_t llama_state_seq_load_file(
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@ -2102,8 +2098,7 @@ def llama_state_seq_load_file(
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n_token_capacity: Union[ctypes.c_size_t, int],
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n_token_count_out: CtypesPointerOrRef[ctypes.c_size_t],
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/,
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) -> int:
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...
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) -> int: ...
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# //
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@ -2366,8 +2361,7 @@ def llama_get_embeddings_seq(
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)
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def llama_token_get_text(
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model: llama_model_p, token: Union[llama_token, int], /
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) -> bytes:
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...
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) -> bytes: ...
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# LLAMA_API float llama_token_get_score(const struct llama_model * model, llama_token token);
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@ -2376,8 +2370,7 @@ def llama_token_get_text(
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)
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def llama_token_get_score(
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model: llama_model_p, token: Union[llama_token, int], /
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) -> float:
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...
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) -> float: ...
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# LLAMA_API enum llama_token_type llama_token_get_type(const struct llama_model * model, llama_token token);
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@ -2386,8 +2379,7 @@ def llama_token_get_score(
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)
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def llama_token_get_type(
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model: llama_model_p, token: Union[llama_token, int], /
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) -> int:
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...
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) -> int: ...
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# // Check if the token is supposed to end generation (end-of-generation, eg. EOS, EOT, etc.)
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@ -2395,9 +2387,7 @@ def llama_token_get_type(
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@ctypes_function(
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"llama_token_is_eog", [llama_model_p_ctypes, llama_token], ctypes.c_bool
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)
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def llama_token_is_eog(
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model: llama_model_p, token: Union[llama_token, int], /
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) -> bool:
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def llama_token_is_eog(model: llama_model_p, token: Union[llama_token, int], /) -> bool:
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"""Check if the token is supposed to end generation (end-of-generation, eg. EOS, EOT, etc.)"""
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...
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@ -2466,20 +2456,17 @@ def llama_token_prefix(model: llama_model_p) -> int:
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# LLAMA_API llama_token llama_token_middle(const struct llama_model * model); // Beginning of infill middle
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@ctypes_function("llama_token_middle", [llama_model_p_ctypes], llama_token)
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def llama_token_middle(model: llama_model_p, /) -> int:
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...
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def llama_token_middle(model: llama_model_p, /) -> int: ...
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# LLAMA_API llama_token llama_token_suffix(const struct llama_model * model); // Beginning of infill suffix
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@ctypes_function("llama_token_suffix", [llama_model_p_ctypes], llama_token)
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def llama_token_suffix(model: llama_model_p, /) -> int:
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...
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def llama_token_suffix(model: llama_model_p, /) -> int: ...
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# LLAMA_API llama_token llama_token_eot (const struct llama_model * model); // End of infill middle
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@ctypes_function("llama_token_eot", [llama_model_p_ctypes], llama_token)
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def llama_token_eot(model: llama_model_p, /) -> int:
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...
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def llama_token_eot(model: llama_model_p, /) -> int: ...
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# //
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@ -2620,8 +2607,7 @@ def llama_chat_apply_template(
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chat: CtypesArray[llama_chat_message],
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n_msg: int,
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/,
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) -> int:
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...
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) -> int: ...
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# //
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@ -3234,8 +3220,7 @@ def llama_beam_search(
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n_past: Union[ctypes.c_int, int],
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n_predict: Union[ctypes.c_int, int],
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/,
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):
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...
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): ...
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# /// @details Build a split GGUF final path for this chunk.
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@ -3354,5 +3339,4 @@ def llama_log_set(
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[ctypes.c_void_p, llama_context_p_ctypes],
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None,
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)
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def llama_dump_timing_info_yaml(stream: ctypes.c_void_p, ctx: llama_context_p, /):
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...
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def llama_dump_timing_info_yaml(stream: ctypes.c_void_p, ctx: llama_context_p, /): ...
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2
vendor/llama.cpp
vendored
2
vendor/llama.cpp
vendored
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@ -1 +1 @@
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Subproject commit 46e12c4692a37bdd31a0432fc5153d7d22bc7f72
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Subproject commit 4dba7e8114d84241c842b986e008af8b88d1a019
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Loading…
Reference in a new issue