History

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_test.go

runner.go: Better abstract vision model integration

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

image_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

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_test.go

runner.go: Handle truncation of tokens for stop sequences

2024-10-09 20:39:04 -07:00

stop.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