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https://github.com/ggerganov/llama.cpp.git
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llama2c : rename function
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6c9c23429b
commit
0d58936686
@ -637,7 +637,7 @@ void load_vocab(const char *filename, Config *config, struct llama_vocab *vocab)
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}
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}
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void stuff_karpathy_weights_into_gg(struct ggml_tensor * gg_weights, const float * karpathy_weights) {
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void convert_weights_ak_to_gg(struct ggml_tensor * gg_weights, const float * karpathy_weights) {
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int ct;
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switch (gg_weights->n_dims){
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case 1:
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@ -674,13 +674,13 @@ void stuff_karpathy_weights_into_gg(struct ggml_tensor * gg_weights, const float
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}
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void save_as_llama_model(struct llama_vocab * vocab, struct my_llama_model * model, TransformerWeights* w, const char * filename) {
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// stuff AK weights into GG weights one by one.
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// convert AK weights into GG weights one by one.
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// w->token_embedding_table -> model->tok_embeddings
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// float* -> struct ggml_tensor
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stuff_karpathy_weights_into_gg(model->tok_embeddings, w->token_embedding_table);
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stuff_karpathy_weights_into_gg(model->output, w->wcls ? w->wcls : w->token_embedding_table);
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convert_weights_ak_to_gg(model->tok_embeddings, w->token_embedding_table);
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convert_weights_ak_to_gg(model->output, w->wcls ? w->wcls : w->token_embedding_table);
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stuff_karpathy_weights_into_gg(model->norm, w->rms_final_weight);
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convert_weights_ak_to_gg(model->norm, w->rms_final_weight);
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//print_row(model->norm, 0);
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// for rms-att-weight
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@ -690,18 +690,18 @@ void save_as_llama_model(struct llama_vocab * vocab, struct my_llama_model * mod
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for (uint32_t i = 0; i < model->hparams.n_layer; ++i){
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auto & layer = model->layers[i];
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// 1d
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stuff_karpathy_weights_into_gg(layer.attention_norm, &w->rms_att_weight[i*row_length]);
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stuff_karpathy_weights_into_gg(layer.ffn_norm , &w->rms_ffn_weight[i*row_length]);
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convert_weights_ak_to_gg(layer.attention_norm, &w->rms_att_weight[i*row_length]);
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convert_weights_ak_to_gg(layer.ffn_norm , &w->rms_ffn_weight[i*row_length]);
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// from 3d matrix layer x dim x dim to 2d matrix dim x dim
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stuff_karpathy_weights_into_gg(layer.wq , &w->wq[i*row_length*row_length]);
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stuff_karpathy_weights_into_gg(layer.wk , &w->wk[i*row_length*row_length]);
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stuff_karpathy_weights_into_gg(layer.wv , &w->wv[i*row_length*row_length]);
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stuff_karpathy_weights_into_gg(layer.wo , &w->wo[i*row_length*row_length]);
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convert_weights_ak_to_gg(layer.wq , &w->wq[i*row_length*row_length]);
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convert_weights_ak_to_gg(layer.wk , &w->wk[i*row_length*row_length]);
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convert_weights_ak_to_gg(layer.wv , &w->wv[i*row_length*row_length]);
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convert_weights_ak_to_gg(layer.wo , &w->wo[i*row_length*row_length]);
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stuff_karpathy_weights_into_gg(layer.w1 , &w->w1[i*row_length*n_ff]);
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stuff_karpathy_weights_into_gg(layer.w2 , &w->w2[i*n_ff*row_length]);
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stuff_karpathy_weights_into_gg(layer.w3 , &w->w3[i*row_length*n_ff]);
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convert_weights_ak_to_gg(layer.w1 , &w->w1[i*row_length*n_ff]);
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convert_weights_ak_to_gg(layer.w2 , &w->w2[i*n_ff*row_length]);
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convert_weights_ak_to_gg(layer.w3 , &w->w3[i*row_length*n_ff]);
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}
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struct gguf_context * ctx = gguf_init_empty();
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