vbatts/llama.cpp
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llama : differentiate the KV dims in the attention (#4657)

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* Add n_key_dim and n_value_dim

Some models use values that are not derived from `n_embd`.
Also remove `n_embd_head` and `n_embd_gqa` because it is not clear
which "head" is referred to (key or value).

Fix issue #4648.

* Fix `llm_build_kqv` to use `n_value_gqa`

* Rebase

* Rename variables

* Fix llm_build_kqv to be more generic wrt n_embd_head_k

* Update default values for n_embd_head_k and n_embd_head_v

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Fix llm_load_tensors: the asserts were not backcompat

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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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postmasters 2024-01-02 03:51:28 -08:00 • committed by GitHub
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gguf-py/gguf/constants.py
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@ -46,6 +46,8 @@ class Keys:
HEAD_COUNT_KV = "{arch}.attention.head_count_kv"
MAX_ALIBI_BIAS = "{arch}.attention.max_alibi_bias"
CLAMP_KQV = "{arch}.attention.clamp_kqv"
KEY_LENGTH = "{arch}.attention.key_length"
VALUE_LENGTH = "{arch}.attention.value_length"
LAYERNORM_EPS = "{arch}.attention.layer_norm_epsilon"
LAYERNORM_RMS_EPS = "{arch}.attention.layer_norm_rms_epsilon"