This is a suite of assorted tools for inspecting and manipulating docker and OCI images for machine learning workloads.
- it does not depend on a local docker daemon; it directly manipulates the layers as tar files
- it works with the image registry directly
- it can modify existing images without downloading layers
- it can attach weights to an existing image
- it works from inside docker
Many subcommands take some or all of the following options:
-t,--token: replicate cog token for pushing tor8.im. Can also be specified asCOG_TOKENenvironment variable.-r,--registry: image registry to push to (by default,r8.im).-h,--help: get help for subcommand
Add a new layer to an existing image, without changing any of the existing layers.
r8im affix --base <base-image> --dest <destination-image> --tar <layer-tar-file>
CAUTION: affix can result in broken images. Because you aren't
building an image using a traditional build process, there's no
guarantees that dependencies will work correctly after manipulating an
image.
Extract weights from an image.
r8im extract <image> [--output file]
If --output is unspecified, weights are emitted to stdout.
Image layers are detected by searching any layer whose command ends
with # weights or starts with COPY . /src, and within those
layers looking for appropriate files in src/weights.
Summarize layers of an image.
r8im layers <image>
Remix layers of an existing image. Takes one model image, and extracts weights from a second image, combining them together into a new image.
r8im remix --base <image-including-tag> --weights <image-including-tag> --dest <image-dest>
CAUTION: remix can result in broken images. Because you aren't
building an image using a traditional build process, there's no
guarantees that dependencies will work correctly after manipulating an
image.
Recompress the layers of an image using zstd.
r8im zstd <image> <dest>