vbatts/llama.cpp
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llama: add support for QRWKV6 model architecture (#11001)

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llama: add support for QRWKV6 model architecture (#11001)

* WIP: Add support for RWKV6Qwen2

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* RWKV: Some graph simplification

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Add support for RWKV6Qwen2 with cpu and cuda GLA

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* RWKV6[QWEN2]: Concat lerp weights together to reduce cpu overhead

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Fix some typos

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* code format changes

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Fix wkv test & add gla test

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Fix cuda warning

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Update README.md

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* Update ggml/src/ggml-cuda/gla.cu

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

* Fix fused lerp weights loading with RWKV6

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* better sanity check skipping for QRWKV6 in llama-quant

thanks @compilade

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
Co-authored-by: compilade <git@compilade.net>

---------

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: compilade <git@compilade.net>
This commit is contained in:
Molly Sophia 2025-01-10 09:58:08 +08:00 • committed by GitHub
parent c6860cc734
commit ee7136c6d1
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GPG key ID: B5690EEEBB952194
23 changed files with 862 additions and 124 deletions
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8
src/llama-model.cpp
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@ -1054,12 +1054,15 @@ void llm_load_hparams(llama_model_loader & ml, llama_model & model) {
}
} break;
case LLM_ARCH_RWKV6:
case LLM_ARCH_RWKV6QWEN2:
{
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps, false);
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps, false);
ml.get_key(LLM_KV_WKV_HEAD_SIZE, hparams.wkv_head_size);
ml.get_key(LLM_KV_TIME_MIX_EXTRA_DIM, hparams.time_mix_extra_dim);
ml.get_key(LLM_KV_TIME_DECAY_EXTRA_DIM, hparams.time_decay_extra_dim);
ml.get_key(LLM_KV_RESCALE_EVERY_N_LAYERS, hparams.rescale_every_n_layers, false);
ml.get_key(LLM_KV_TOKEN_SHIFT_COUNT, hparams.token_shift_count, false);
switch (hparams.n_layer) {
case 24: model.type = e_model::MODEL_1_6B; break;
@ -1070,6 +1073,7 @@ void llm_load_hparams(llama_model_loader & ml, llama_model & model) {
default: model.type = e_model::MODEL_UNKNOWN;
} break;
case 61: model.type = e_model::MODEL_14B; break;
case 64: model.type = e_model::MODEL_32B; break;
default: model.type = e_model::MODEL_UNKNOWN;
}
} break;
@ -2064,6 +2068,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
case LLM_ARCH_T5ENCODER:
case LLM_ARCH_JAIS:
case LLM_ARCH_RWKV6:
case LLM_ARCH_RWKV6QWEN2:
case LLM_ARCH_WAVTOKENIZER_DEC:
return LLAMA_ROPE_TYPE_NONE;
@ -2208,6 +2213,7 @@ bool llama_model_is_recurrent(const struct llama_model * model) {
switch (model->arch) {
case LLM_ARCH_MAMBA: return true;
case LLM_ARCH_RWKV6: return true;
case LLM_ARCH_RWKV6QWEN2: return true;
default: return false;
}
}