Update llama.cpp
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2 changed files with 23 additions and 1 deletions
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@ -155,6 +155,7 @@ llama_progress_callback = ctypes.CFUNCTYPE(None, c_float, c_void_p)
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# int n_gpu_layers; // number of layers to store in VRAM
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# int main_gpu; // the GPU that is used for scratch and small tensors
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# float tensor_split[LLAMA_MAX_DEVICES]; // how to split layers across multiple GPUs
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# bool low_vram; // if true, reduce VRAM usage at the cost of performance
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# int seed; // RNG seed, -1 for random
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# bool f16_kv; // use fp16 for KV cache
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@ -177,6 +178,7 @@ class llama_context_params(Structure):
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("n_gpu_layers", c_int),
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("main_gpu", c_int),
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("tensor_split", c_float * LLAMA_MAX_DEVICES.value),
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("low_vram", c_bool),
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("seed", c_int),
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("f16_kv", c_bool),
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(
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@ -555,6 +557,26 @@ _lib.llama_n_embd.argtypes = [llama_context_p]
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_lib.llama_n_embd.restype = c_int
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# // Get the vocabulary as output parameters.
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# // Returns number of results.
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# LLAMA_API int llama_get_vocab(
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# const struct llama_context * ctx,
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# const char * * strings,
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# float * scores,
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# int capacity);
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def llama_get_vocab(
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ctx: llama_context_p,
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strings, # type: Array[c_char_p] # type: ignore
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scores, # type: Array[c_float] # type: ignore
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capacity: c_int,
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) -> int:
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return _lib.llama_get_vocab(ctx, strings, scores, capacity)
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_lib.llama_get_vocab.argtypes = [llama_context_p, c_char_p, c_float, c_int]
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_lib.llama_get_vocab.restype = c_int
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# Token logits obtained from the last call to llama_eval()
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# The logits for the last token are stored in the last row
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# Can be mutated in order to change the probabilities of the next token
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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 4de0334f5cabf4696eced2e5d6e279fdfaa6c0f2
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Subproject commit 254a7a7a5ff4c874ff8488f1f5cbdd7e9c89d682
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