Merge branch 'main' of https://github.com/abetlen/llama-cpp-python into main
This commit is contained in:
commit
a6457ba74b
7 changed files with 51 additions and 24 deletions
4
.github/workflows/build-and-release.yaml
vendored
4
.github/workflows/build-and-release.yaml
vendored
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@ -29,7 +29,7 @@ jobs:
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python -m pip install -e .[all]
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- name: Build wheels
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uses: pypa/cibuildwheel@v2.18.0
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uses: pypa/cibuildwheel@v2.18.1
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env:
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# disable repair
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CIBW_REPAIR_WHEEL_COMMAND: ""
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@ -56,7 +56,7 @@ jobs:
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platforms: linux/arm64
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- name: Build wheels
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uses: pypa/cibuildwheel@v2.18.0
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uses: pypa/cibuildwheel@v2.18.1
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env:
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CIBW_SKIP: "*musllinux* pp*"
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CIBW_REPAIR_WHEEL_COMMAND: ""
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8
Makefile
8
Makefile
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@ -13,7 +13,13 @@ build:
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python3 -m pip install --verbose -e .
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build.debug:
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CMAKE_ARGS="-DCMAKE_BUILD_TYPE=Debug" python3 -m pip install --verbose --config-settings=cmake.verbose=true --config-settings=logging.level=INFO --config-settings=install.strip=false --editable .
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python3 -m pip install \
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--verbose \
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--config-settings=cmake.verbose=true \
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--config-settings=logging.level=INFO \
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--config-settings=install.strip=false \
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--config-settings=cmake.args="-DCMAKE_BUILD_TYPE=Debug;-DCMAKE_C_FLAGS='-ggdb -O0';-DCMAKE_CXX_FLAGS='-ggdb -O0'" \
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--editable .
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build.cuda:
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CMAKE_ARGS="-DLLAMA_CUDA=on" python3 -m pip install --verbose -e .
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@ -6,6 +6,7 @@ import uuid
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import time
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import json
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import ctypes
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import typing
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import fnmatch
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import multiprocessing
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@ -249,13 +250,13 @@ class Llama:
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self._kv_overrides_array[i].key = k.encode("utf-8")
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if isinstance(v, bool):
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self._kv_overrides_array[i].tag = llama_cpp.LLAMA_KV_OVERRIDE_TYPE_BOOL
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self._kv_overrides_array[i].value.bool_value = v
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self._kv_overrides_array[i].value.val_bool = v
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elif isinstance(v, int):
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self._kv_overrides_array[i].tag = llama_cpp.LLAMA_KV_OVERRIDE_TYPE_INT
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self._kv_overrides_array[i].value.int_value = v
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self._kv_overrides_array[i].value.val_i64 = v
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elif isinstance(v, float):
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self._kv_overrides_array[i].tag = llama_cpp.LLAMA_KV_OVERRIDE_TYPE_FLOAT
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self._kv_overrides_array[i].value.float_value = v
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self._kv_overrides_array[i].value.val_f64 = v
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elif isinstance(v, str): # type: ignore
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v_bytes = v.encode("utf-8")
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if len(v_bytes) > 128: # TODO: Make this a constant
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@ -263,10 +264,12 @@ class Llama:
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v_bytes = v_bytes.ljust(128, b"\0")
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self._kv_overrides_array[i].tag = llama_cpp.LLAMA_KV_OVERRIDE_TYPE_STR
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# copy min(v_bytes, 128) to str_value
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address = typing.cast(int, ctypes.addressof(self._kv_overrides_array[i].value) + llama_cpp.llama_model_kv_override_value.val_str.offset)
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buffer_start = ctypes.cast(address, ctypes.POINTER(ctypes.c_char))
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ctypes.memmove(
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self._kv_overrides_array[i].value.str_value,
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buffer_start,
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v_bytes,
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min(len(v_bytes), 128),
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128,
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)
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else:
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raise ValueError(f"Unknown value type for {k}: {v}")
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@ -3098,7 +3098,7 @@ class NanoLlavaChatHandler(Llava15ChatHandler):
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"{% endif %}"
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)
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class Llama3VisionAlpha(Llava15ChatHandler):
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class Llama3VisionAlphaChatHandler(Llava15ChatHandler):
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# question = "<image>" + q
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# prompt = f"<|start_header_id|>user<|end_header_id|>\n\n{question}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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@ -3159,6 +3159,10 @@ class Llama3VisionAlpha(Llava15ChatHandler):
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"{% endif %}"
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)
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# alias
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Llama3VisionAlpha = Llama3VisionAlphaChatHandler
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@register_chat_completion_handler("chatml-function-calling")
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def chatml_function_calling(
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llama: llama.Llama,
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@ -3193,7 +3197,6 @@ def chatml_function_calling(
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llama_types.CreateChatCompletionResponse,
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Iterator[llama_types.CreateChatCompletionStreamResponse],
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]:
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print(logprobs)
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function_calling_template = (
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"{% for message in messages %}"
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"<|im_start|>{{ message.role }}\n"
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@ -300,6 +300,7 @@ LLAMA_VOCAB_TYPE_WPM = 3
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# LLAMA_VOCAB_PRE_TYPE_QWEN2 = 11,
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# LLAMA_VOCAB_PRE_TYPE_OLMO = 12,
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# LLAMA_VOCAB_PRE_TYPE_DBRX = 13,
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# LLAMA_VOCAB_PRE_TYPE_SMAUG = 14,
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# };
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LLAMA_VOCAB_PRE_TYPE_DEFAULT = 0
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LLAMA_VOCAB_PRE_TYPE_LLAMA3 = 1
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@ -315,6 +316,7 @@ LLAMA_VOCAB_PRE_TYPE_STABLELM2 = 10
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LLAMA_VOCAB_PRE_TYPE_QWEN2 = 11
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LLAMA_VOCAB_PRE_TYPE_OLMO = 12
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LLAMA_VOCAB_PRE_TYPE_DBRX = 13
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LLAMA_VOCAB_PRE_TYPE_SMAUG = 14
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# // note: these values should be synchronized with ggml_rope
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@ -611,17 +613,17 @@ LLAMA_KV_OVERRIDE_TYPE_STR = 3
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# };
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class llama_model_kv_override_value(ctypes.Union):
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_fields_ = [
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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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("val_i64", ctypes.c_int64),
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("val_f64", ctypes.c_double),
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("val_bool", ctypes.c_bool),
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("val_str", 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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val_i64: int
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val_f64: float
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val_bool: bool
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val_str: bytes
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class llama_model_kv_override(ctypes.Structure):
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@ -718,6 +720,8 @@ class llama_model_params(ctypes.Structure):
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]
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# // NOTE: changing the default values of parameters marked as [EXPERIMENTAL] may cause crashes or incorrect results in certain configurations
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# // https://github.com/ggerganov/llama.cpp/pull/7544
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# struct llama_context_params {
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# uint32_t seed; // RNG seed, -1 for random
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# uint32_t n_ctx; // text context, 0 = from model
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@ -744,15 +748,14 @@ class llama_model_params(ctypes.Structure):
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# ggml_backend_sched_eval_callback cb_eval;
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# void * cb_eval_user_data;
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# enum ggml_type type_k; // data type for K cache
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# enum ggml_type type_v; // data type for V cache
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# enum ggml_type type_k; // data type for K cache [EXPERIMENTAL]
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# enum ggml_type type_v; // data type for V cache [EXPERIMENTAL]
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# // Keep the booleans together to avoid misalignment during copy-by-value.
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# bool logits_all; // the llama_decode() call computes all logits, not just the last one (DEPRECATED - set llama_batch.logits instead)
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# bool embeddings; // if true, extract embeddings (together with logits)
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# bool offload_kqv; // whether to offload the KQV ops (including the KV cache) to GPU
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# bool flash_attn; // whether to use flash attention
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# bool flash_attn; // whether to use flash attention [EXPERIMENTAL]
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# // Abort callback
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# // if it returns true, execution of llama_decode() will be aborted
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@ -2454,6 +2457,16 @@ def llama_token_is_eog(model: llama_model_p, token: Union[llama_token, int], /)
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...
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# // Identify if Token Id is a control token or a render-able token
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# LLAMA_API bool llama_token_is_control(const struct llama_model * model, llama_token token);
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@ctypes_function(
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"llama_token_is_control", [llama_model_p_ctypes, llama_token], ctypes.c_bool
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)
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def llama_token_is_control(model: llama_model_p, token: Union[llama_token, int], /) -> bool:
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"""Identify if Token Id is a control token or a render-able token"""
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...
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# // Special tokens
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@ -183,7 +183,7 @@ class LlamaProxy:
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num_pred_tokens=settings.draft_model_num_pred_tokens
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)
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kv_overrides: Optional[Dict[str, Union[bool, int, float]]] = None
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kv_overrides: Optional[Dict[str, Union[bool, int, float, str]]] = None
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if settings.kv_overrides is not None:
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assert isinstance(settings.kv_overrides, list)
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kv_overrides = {}
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kv_overrides[key] = int(value)
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elif value_type == "float":
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kv_overrides[key] = float(value)
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elif value_type == "str":
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kv_overrides[key] = value
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else:
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raise ValueError(f"Unknown value type {value_type}")
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2
vendor/llama.cpp
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2
vendor/llama.cpp
vendored
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@ -1 +1 @@
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Subproject commit 0df0aa8e43c3378975269a51f9b876c8692e70da
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Subproject commit 504f0c340f6b5e04de682f6ddefdd3b81208df5d
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