Buckets:
| void llama_model_jina_bert_v3::load_arch_hparams(llama_model_loader & ml) { | |
| ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps); | |
| switch (hparams.n_layer()) { | |
| case 24: | |
| type = LLM_TYPE_558M; break; | |
| default: type = LLM_TYPE_UNKNOWN; | |
| } | |
| } | |
| void llama_model_jina_bert_v3::load_arch_tensors(llama_model_loader &) { | |
| LLAMA_LOAD_LOCALS; | |
| if (n_token_types == 0) { | |
| throw std::runtime_error(arch_name() + " model needs to define token type count"); | |
| } | |
| tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0); | |
| type_embd = create_tensor(tn(LLM_TENSOR_TOKEN_TYPES, "weight"), {n_embd, n_token_types}, TENSOR_NOT_REQUIRED); | |
| tok_norm = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD_NORM, "weight", 0), {n_embd}, 0); | |
| tok_norm_b = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD_NORM, "bias", 0), {n_embd}, 0); | |
| for (int i = 0; i < n_layer; ++i) { | |
| auto & layer = layers[i]; | |
| create_tensor_qkv(layer, i, n_embd, n_embd, n_embd_gqa, n_embd_gqa, 0); | |
| layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0); | |
| layer.wo_b = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "bias", i), {n_embd}, TENSOR_NOT_REQUIRED); | |
| layer.attn_out_norm = create_tensor(tn(LLM_TENSOR_ATTN_OUT_NORM, "weight", i), {n_embd}, 0); | |
| layer.attn_out_norm_b = create_tensor(tn(LLM_TENSOR_ATTN_OUT_NORM, "bias", i), {n_embd}, 0); | |
| layer.ffn_up = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}, 0); | |
| layer.ffn_up_b = create_tensor(tn(LLM_TENSOR_FFN_UP, "bias", i), {n_ff}, TENSOR_NOT_REQUIRED); | |
| 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}, TENSOR_NOT_REQUIRED); | |
| layer.layer_out_norm = create_tensor(tn(LLM_TENSOR_LAYER_OUT_NORM, "weight", i), {n_embd}, 0); | |
| layer.layer_out_norm_b = create_tensor(tn(LLM_TENSOR_LAYER_OUT_NORM, "bias", i), {n_embd}, 0); | |
| } | |
| } | |
| std::unique_ptr<llm_graph_context> llama_model_jina_bert_v3::build_arch_graph(const llm_graph_params & params) const { | |
| return std::make_unique<graph>(*this, params); | |
| } | |
Xet Storage Details
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- 2.3 kB
- Xet hash:
- c48009ed3c23b26c3d9f1b9119fd9f49e375c69cb60cf76d5e7598a60411a80c
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