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27 changes: 0 additions & 27 deletions convert_hf_to_gguf.py
Original file line number Diff line number Diff line change
Expand Up @@ -4798,25 +4798,6 @@ def prepare_tensors(self):
class JinaBertV2Model(BertModel):
model_arch = gguf.MODEL_ARCH.JINA_BERT_V2

def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.intermediate_size = self.hparams["intermediate_size"]

def get_tensors(self):
for name, data in super().get_tensors():
if 'gated_layer' in name:
d1 = data[:self.intermediate_size, :]
name1 = name.replace('gated_layers', 'gated_layers_w')
name1 = name1.replace('up_gated_layer', 'gated_layers_v')
d2 = data[self.intermediate_size:, :]
name2 = name.replace('gated_layers', 'gated_layers_v')
name2 = name2.replace('up_gated_layer', 'gated_layers_w')
yield name1, d1
yield name2, d2
continue

yield name, data

def set_vocab(self):
tokenizer_class = 'BertTokenizer'
with open(self.dir_model / "tokenizer_config.json", "r", encoding="utf-8") as f:
Expand All @@ -4832,14 +4813,6 @@ def set_vocab(self):
self.gguf_writer.add_add_bos_token(True)
self.gguf_writer.add_add_eos_token(True)

def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
# if name starts with "bert.", remove the prefix
# e.g. https://huggingface.co/jinaai/jina-reranker-v1-tiny-en
if name.startswith("bert."):
name = name[5:]

return super().modify_tensors(data_torch, name, bid)


@ModelBase.register("OpenELMForCausalLM")
class OpenELMModel(TextModel):
Expand Down
6 changes: 4 additions & 2 deletions gguf-py/gguf/tensor_mapping.py
Original file line number Diff line number Diff line change
Expand Up @@ -333,7 +333,9 @@ class TensorNameMap:
"encoder.layers.{bid}.mlp.fc11", # nomic-bert
"encoder.layers.{bid}.mlp.fc1", # nomic-bert-moe
"model.layers.{bid}.mlp.c_fc", # starcoder2
"encoder.layer.{bid}.mlp.gated_layers_v", # jina-bert-v2
"encoder.layer.{bid}.mlp.gated_layers_v", # jina-bert-v2 (split up/gate, no longer used)
"encoder.layer.{bid}.mlp.gated_layers", # jina-bert-v2 (GEGLU)
"encoder.layer.{bid}.mlp.up_gated_layer", # jina-v2-code (GEGLU)
"model.layers.{bid}.residual_mlp.w3", # arctic
"encoder.layers.{bid}.mlp.dense_h_to_4h", # chatglm
"transformer.h.{bid}.mlp.c_fc_1", # exaone
Expand Down Expand Up @@ -370,7 +372,7 @@ class TensorNameMap:
"model.layers.layers.{bid}.mlp.gate_proj", # plamo
"model.layers.{bid}.feed_forward.w1", # internlm2
"encoder.layers.{bid}.mlp.fc12", # nomic-bert
"encoder.layer.{bid}.mlp.gated_layers_w", # jina-bert-v2
"encoder.layer.{bid}.mlp.gated_layers_w", # jina-bert-v2 (split up/gate, no longer used)
"transformer.h.{bid}.mlp.linear_1", # refact
"model.layers.{bid}.residual_mlp.w1", # arctic
"transformer.h.{bid}.mlp.c_fc_0", # exaone
Expand Down
3 changes: 2 additions & 1 deletion src/llama-graph.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -650,6 +650,7 @@ ggml_tensor * llm_graph_context::build_ffn(
{
// Project to 4h. If using swiglu double the output width, see https://arxiv.org/pdf/2002.05202.pdf
int64_t split_point = cur->ne[0] / 2;
// TODO: these conts should not be needed, see https://github.com/ggml-org/llama.cpp/pull/14090#discussion_r2137437217
ggml_tensor * x0 = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, split_point, cur->ne[1], cur->nb[1], 0));
ggml_tensor * x1 = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, split_point, cur->ne[1], cur->nb[1], split_point * ggml_element_size(cur)));

Expand All @@ -663,7 +664,7 @@ ggml_tensor * llm_graph_context::build_ffn(
{
// Split into two equal parts
int64_t split_point = cur->ne[0] / 2;
// TODO: these conts should not be needed
// TODO: these conts should not be needed, see https://github.com/ggml-org/llama.cpp/pull/14090#discussion_r2137437217
ggml_tensor * x0 = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, split_point, cur->ne[1], cur->nb[1], 0));
ggml_tensor * x1 = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, split_point, cur->ne[1], cur->nb[1], split_point * ggml_element_size(cur)));

Expand Down
6 changes: 3 additions & 3 deletions src/llama-model.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -2224,8 +2224,8 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
layer.attn_norm_2 = create_tensor(tn(LLM_TENSOR_ATTN_NORM_2, "weight", i), {n_embd}, TENSOR_NOT_REQUIRED);
layer.attn_norm_2_b = create_tensor(tn(LLM_TENSOR_ATTN_NORM_2, "bias", i), {n_embd}, TENSOR_NOT_REQUIRED);

layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}, 0);
layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, 0);
layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED);
layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, layer.ffn_gate ? n_ff : n_ff * 2}, 0);

layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}, 0);
layer.ffn_down_b = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "bias", i), {n_embd}, 0);
Expand Down Expand Up @@ -6043,7 +6043,7 @@ struct llm_build_bert : public llm_graph_context {
model.layers[il].ffn_gate, NULL, NULL,
model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
NULL,
LLM_FFN_GELU, LLM_FFN_PAR, il);
model.layers[il].ffn_gate ? LLM_FFN_GELU : LLM_FFN_GEGLU, LLM_FFN_PAR, il);
cb(cur, "ffn_out", il);
} else {
cur = build_ffn(cur,
Expand Down