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llama.cpp/examples/embedding
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Douglas Hanley 80ea089d77
llama : allow pooled embeddings on any model (#7477) 
* create append_pooling operation; allow to specify attention_type; add last token pooling; update examples

* find result_norm/result_embd tensors properly; update output allocation logic

* only use embd output for pooling_type NONE

* get rid of old causal_attn accessor

* take out attention_type; add in llama_set_embeddings

* bypass logits when doing non-NONE pooling
2024-06-21 08:38:22 +03:00
..
CMakeLists.txt build: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809) 2024-06-13 00:41:52 +01:00
embedding.cpp llama : allow pooled embeddings on any model (#7477) 2024-06-21 08:38:22 +03:00
README.md build: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809) 2024-06-13 00:41:52 +01:00

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.):

./llama-embedding -m ./path/to/model --log-disable -p "Hello World!" 2>/dev/null

Windows:

llama-embedding.exe -m ./path/to/model --log-disable -p "Hello World!" 2>$null

The above command will output space-separated float values.