baalajimaestro/llama.cpp
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add mul_mat_q parameter

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This also fixes a crash when loading the 70b llama2 model on MacOS with
metal and `n_gpu_layers=1`
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bretello 2023-08-03 18:22:52 +02:00
parent 91bf8fac1b
commit 39978ccaf5
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llama_cpp/llama_cpp.py
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@ -181,6 +181,7 @@ llama_progress_callback = ctypes.CFUNCTYPE(None, c_float, c_void_p)
# // Keep the booleans together to avoid misalignment during copy-by-value. # // Keep the booleans together to avoid misalignment during copy-by-value.
# bool low_vram; // if true, reduce VRAM usage at the cost of performance # bool low_vram; // if true, reduce VRAM usage at the cost of performance
# bool mul_mat_q; // if true, use experimental mul_mat_q kernels
# bool f16_kv; // use fp16 for KV cache # bool f16_kv; // use fp16 for KV cache
# bool logits_all; // the llama_eval() call computes all logits, not just the last one # bool logits_all; // the llama_eval() call computes all logits, not just the last one
# bool vocab_only; // only load the vocabulary, no weights # bool vocab_only; // only load the vocabulary, no weights
@ -203,6 +204,7 @@ class llama_context_params(Structure):
("progress_callback", llama_progress_callback), ("progress_callback", llama_progress_callback),
("progress_callback_user_data", c_void_p), ("progress_callback_user_data", c_void_p),
("low_vram", c_bool), ("low_vram", c_bool),
("mul_mat_q", c_bool),
("f16_kv", c_bool), ("f16_kv", c_bool),
("logits_all", c_bool), ("logits_all", c_bool),
("vocab_only", c_bool), ("vocab_only", c_bool),