mirror of
https://github.com/dogkeeper886/ollama37.git
synced 2025-12-10 07:46:59 +00:00
94ab428e3f
Currently, when the backend is created, the tensors are loaded at the same time, which is a slow operation. This separates them to be two steps: - Create backend, including enumerating tensors and memory allocation - Loading tensor data This allows more flexibility in managing model loading.
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