Modelz Alpaca-LoRA

alpaca-lora with Dockerfile and build.envd, code almost from deep-driver, thanks for all works.

Build

In the Dockerfile, you need to define the instructions for building a Docker image that encapsulates the server code and its dependencies.

In most cases, you could use the template in the repository.

docker build -t docker.io/USER/IMAGE .
docker push docker.io/USER/IMAGE

# GPU
docker build -t docker.io/USER/IMAGE -f Dockerfile.gpu .
docker push docker.io/USER/IMAGE

On the other hand, a build.envd is a simplified alternative to a Dockerfile. It provides python-based interfaces that contains configuration settings for building a image.

It is easier to use than a Dockerfile as it involves specifying only the dependencies of your machine learning model, not the instructions for CUDA, conda, and other system-level dependencies.

envd build --output type=image,name=docker.io/USER/IMAGE,push=true
# GPU
envd build --output type=image,name=docker.io/USER/IMAGE,push=true -f :build_gpu

Deploy

Please refer to the Modelz documentation for more details.