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llama : rework embeddings logic (#14208)
* llama : rework embeddings logic ggml-ci * cont : fix rerank ggml-ci * cont : engrish [no ci] * cont : fix rerank ggml-ci * server : support both embeddings and completions with single model ggml-ci * cont : avoid embeddings_org ggml-ci
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@ -988,10 +988,6 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
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params.tensor_buft_overrides.push_back({nullptr, nullptr});
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}
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if (params.reranking && params.embedding) {
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throw std::invalid_argument("error: either --embedding or --reranking can be specified, but not both");
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}
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if (!params.chat_template.empty() && !common_chat_verify_template(params.chat_template, params.use_jinja)) {
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throw std::runtime_error(string_format(
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"error: the supplied chat template is not supported: %s%s\n",
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@ -2747,9 +2743,10 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_EMBEDDINGS"));
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add_opt(common_arg(
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{"--reranking", "--rerank"},
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string_format("enable reranking endpoint on server (default: %s)", params.reranking ? "enabled" : "disabled"),
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string_format("enable reranking endpoint on server (default: %s)", "disabled"),
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[](common_params & params) {
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params.reranking = true;
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params.embedding = true;
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params.pooling_type = LLAMA_POOLING_TYPE_RANK;
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}
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).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_RERANKING"));
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add_opt(common_arg(
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