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https://github.com/ikawrakow/ik_llama.cpp.git
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Add mtmd: mtmd.cpp compiles
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@@ -334,10 +334,10 @@ private:
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std::string token_to_piece(const llama_vocab * vocab, llama_token token, bool special) {
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std::string piece;
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piece.resize(piece.capacity()); // using string internal cache, 15 bytes + '\n'
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const int n_chars = llama_token_to_piece(vocab, token, &piece[0], piece.size(), 0, special);
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const int n_chars = llama_vocab_token_to_piece(vocab, token, &piece[0], piece.size(), 0, special);
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if (n_chars < 0) {
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piece.resize(-n_chars);
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int check = llama_token_to_piece(vocab, token, &piece[0], piece.size(), 0, special);
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int check = llama_vocab_token_to_piece(vocab, token, &piece[0], piece.size(), 0, special);
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GGML_ASSERT(check == -n_chars);
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} else {
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piece.resize(n_chars);
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@@ -720,10 +720,10 @@ struct mtmd_tokenizer {
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// upper limit for the number of tokens
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int n_tokens = text.length() + 2 * add_special;
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std::vector<llama_token> result(n_tokens);
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n_tokens = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
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n_tokens = llama_vocab_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
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if (n_tokens < 0) {
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result.resize(-n_tokens);
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int check = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
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int check = llama_vocab_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
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GGML_ASSERT(check == -n_tokens);
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} else {
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result.resize(n_tokens);
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