ci : update ".bin" to ".gguf" extension
ggml-ci
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7 changed files with 42 additions and 42 deletions
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@ -52,7 +52,7 @@ struct gpt_params {
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std::string cfg_negative_prompt; // string to help guidance
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float cfg_scale = 1.f; // How strong is guidance
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std::string model = "models/7B/ggml-model.bin"; // model path
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std::string model = "models/7B/ggml-model-f16.bin"; // model path
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std::string model_alias = "unknown"; // model alias
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std::string prompt = "";
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std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state
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@ -2,7 +2,7 @@
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//
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// - First, export a LLaMA graph:
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//
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// $ ./bin/main -m ../models/7B/ggml-model-q4_0.bin --export
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// $ ./bin/main -m ../models/7B/ggml-model-q4_0.gguf --export
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//
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// - Run this tool to evaluate the exported graph:
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//
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@ -5,7 +5,7 @@ This example demonstrates a simple HTTP API server and a simple web front end to
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Command line options:
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- `--threads N`, `-t N`: Set the number of threads to use during computation.
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- `-m FNAME`, `--model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.bin`).
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- `-m FNAME`, `--model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`).
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- `-m ALIAS`, `--alias ALIAS`: Set an alias for the model. The alias will be returned in API responses.
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- `-c N`, `--ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference. The size may differ in other models, for example, baichuan models were build with a context of 4096.
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- `-ngl N`, `--n-gpu-layers N`: When compiled with appropriate support (currently CLBlast or cuBLAS), this option allows offloading some layers to the GPU for computation. Generally results in increased performance.
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@ -48,14 +48,12 @@ To get started right away, run the following command, making sure to use the cor
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### Unix-based systems (Linux, macOS, etc.):
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```bash
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./server -m models/7B/ggml-model.bin -c 2048
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./server -m models/7B/ggml-model.gguf -c 2048
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```
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### Windows:
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```powershell
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server.exe -m models\7B\ggml-model.bin -c 2048
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```
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The above command will start a server that by default listens on `127.0.0.1:8080`.
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You can consume the endpoints with Postman or NodeJS with axios library. You can visit the web front end at the same url.
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