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The GGML flash attention kernel has specific requirements for padding and permutation. This adds support to the KV cache for conforming to these requirements so that flash attention can be enabled. Flash attention can be used in the same situations as the llama engine and is enabled by the user in the same way.
runner
Note: this is a work in progress
A minimial runner for loading a model and running inference via a http web server.
./runner -model <model binary>
Completion
curl -X POST -H "Content-Type: application/json" -d '{"prompt": "hi"}' http://localhost:8080/completion
Embeddings
curl -X POST -H "Content-Type: application/json" -d '{"prompt": "turn me into an embedding"}' http://localhost:8080/embedding