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llama.cpp
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Merge branch 'add-fh1-rebased' of https://github.com/tiiuae/llama.cpp-public into add-fh1-rebased

This commit is contained in:
ibrahimkhadraoui 2025-07-08 13:29:54 +04:00
parent 9b92648302 90ddf2412a
commit 7edf380090
3 changed files with 5 additions and 5 deletions
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2
src/llama-arch.cpp
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@ -129,7 +129,7 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
{ LLM_KV_EMBEDDING_SCALE, "%s.embedding_scale" }, { LLM_KV_EMBEDDING_SCALE, "%s.embedding_scale" },
{ LLM_KV_TOKEN_SHIFT_COUNT, "%s.token_shift_count" }, { LLM_KV_TOKEN_SHIFT_COUNT, "%s.token_shift_count" },
{ LLM_KV_INTERLEAVE_MOE_LAYER_STEP, "%s.interleave_moe_layer_step" }, { LLM_KV_INTERLEAVE_MOE_LAYER_STEP, "%s.interleave_moe_layer_step" },
{ LLM_KV_ATTENTION_HEAD_COUNT, "%s.attention.head_count" }, { LLM_KV_ATTENTION_HEAD_COUNT, "%s.attention.head_count" },
{ LLM_KV_ATTENTION_HEAD_COUNT_KV, "%s.attention.head_count_kv" }, { LLM_KV_ATTENTION_HEAD_COUNT_KV, "%s.attention.head_count_kv" },
{ LLM_KV_ATTENTION_MAX_ALIBI_BIAS, "%s.attention.max_alibi_bias" }, { LLM_KV_ATTENTION_MAX_ALIBI_BIAS, "%s.attention.max_alibi_bias" },

4
src/llama-hparams.cpp
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@ -74,8 +74,8 @@ uint32_t llama_hparams::n_embd_r() const {
// TODO: maybe support other convolution strides than 1 // TODO: maybe support other convolution strides than 1
// NOTE: since the first column of the conv_state is shifted out each time, it's not actually needed // NOTE: since the first column of the conv_state is shifted out each time, it's not actually needed
// Corresponds to Mamba's conv_states size // Corresponds to Mamba's conv_states size
// check if the architecture is using d_ssm // check if the architecture is using d_ssm
return (ssm_d_conv > 0 ? ssm_d_conv - 1 : 0) * (ssm_d_inner + 2*ssm_n_group*ssm_d_state); return (ssm_d_conv > 0 ? ssm_d_conv - 1 : 0) * (ssm_d_inner + 2*ssm_n_group*ssm_d_state);
} }

4
src/llama-model.cpp
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@ -4600,7 +4600,7 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
if (output == NULL) { if (output == NULL) {
output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED); output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
} }
for (int i = 0; i < n_layer; ++i) { for (int i = 0; i < n_layer; ++i) {
auto & layer = layers[i]; auto & layer = layers[i];
layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0); layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);
@ -14738,7 +14738,7 @@ struct llm_build_falcon_h1 : public llm_graph_context {
inpSA = ggml_add(ctx0, cur, inpSA); inpSA = ggml_add(ctx0, cur, inpSA);
cb(cur, "layer_out", il); cb(cur, "layer_out", il);
if (il == n_layer - 1 && inp_out_ids) { if (il == n_layer - 1 && inp_out_ids) {
cur = ggml_get_rows(ctx0, cur, inp_out_ids); cur = ggml_get_rows(ctx0, cur, inp_out_ids);
inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids); inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
} }