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ollama/llama/runner
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Jesse Gross c826e57475 runner.go: Better abstract vision model integration 
-Update mllama to take the cross attention state as embeddings in
a batch, more similar to how Llava handles it. This improves
integration with the input cache.
-Pass locations in a prompt for embeddings using tags similar to Llava.
-Abstract interface to vision models so the main runner accesses Clip
and Mllama similarly

Co-authored-by: Michael Yang <mxyng@pm.me>
2024-10-30 14:53:43 -07:00
..
cache.go runner.go: Better abstract vision model integration 2024-10-30 14:53:43 -07:00
cache_test.go runner.go: Better abstract vision model integration 2024-10-30 14:53:43 -07:00
image.go runner.go: Better abstract vision model integration 2024-10-30 14:53:43 -07:00
image_test.go runner.go: Better abstract vision model integration 2024-10-30 14:53:43 -07:00
README.md Re-introduce the llama package (#5034) 2024-10-08 08:53:54 -07:00
requirements.go Re-introduce the llama package (#5034) 2024-10-08 08:53:54 -07:00
runner.go runner.go: Better abstract vision model integration 2024-10-30 14:53:43 -07:00
stop.go runner.go: Handle truncation of tokens for stop sequences 2024-10-09 20:39:04 -07:00
stop_test.go runner.go: Handle truncation of tokens for stop sequences 2024-10-09 20:39:04 -07:00

README.md

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/embeddings