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* llama.cpp : split llama_context_params into model and context params ggml-ci * fix metal build * fix freq_base/scale default to model value * llama-bench : keep the same model between tests when possible * move n_threads to llama_context_params, add n_threads_batch * fix mpi build * remove kv_size(), cuda scratch fixes * remove low-vram option * add n_threads_batch to system info, refactor to get_system_info() * add documentation about --threads-batch to the READMEs * llama-bench fix * main : fix rope freq/scale warning * llama.cpp : add llama_get_model common : add llama_tokenize from model * remove duplicated ctx/model functions ggml-ci * cuda : print total VRAM used |
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| CMakeLists.txt | ||
| embedding.cpp | ||
| README.md | ||
llama.cpp/example/embedding
This example demonstrates generate high-dimensional embedding vector of a given text with llama.cpp.
Quick Start
To get started right away, run the following command, making sure to use the correct path for the model you have:
Unix-based systems (Linux, macOS, etc.):
./embedding -m ./path/to/model --log-disable -p "Hello World!" 2>/dev/null
Windows:
embedding.exe -m ./path/to/model --log-disable -p "Hello World!" 2>$null
The above command will output space-separated float values.