Skip to main content

JAX library for optimization and export of models for use with the UZU inference engine.

Project description

Mirai

Listen to our podcast View our deck Discord Contact us Read docs License

lalamo

A set of tools for adapting Large Language Models to on-device inference using the uzu inference engine.

Quick Start

To get the list of supported models, run:

uv run lalamo list-models

To convert a model, run:

uv run lalamo convert MODEL_REPO

Note: on some CPU platform you may be getting an error saying The precision 'F16_F16_F32' is not supported by dot_general on CPU. This is due to a bug in XLA, which causes matmuls inside jax.jit not work correctly on CPUs. The workaround is to set the environment variable JAX_DISABLE_JIT=1 when running the conversion.

After that, you can find the converted model in the models folder. For more options see uv run lalamo convert --help.

Model Support

To add support for a new model, write the corresponding ModelSpec, as shown in the example below:

ModelSpec(
    vendor="Google",
    family="Gemma-3",
    name="Gemma-3-1B-Instruct",
    size="1B",
    quantization=None,
    repo="google/gemma-3-1b-it",
    config_type=HFGemma3TextConfig,
    weights_type=WeightsType.SAFETENSORS,
)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lalamo-0.6.1.tar.gz (86.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lalamo-0.6.1-py3-none-any.whl (129.1 kB view details)

Uploaded Python 3

File details

Details for the file lalamo-0.6.1.tar.gz.

File metadata

  • Download URL: lalamo-0.6.1.tar.gz
  • Upload date:
  • Size: 86.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.26 {"installer":{"name":"uv","version":"0.9.26","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for lalamo-0.6.1.tar.gz
Algorithm Hash digest
SHA256 ab67489a8ba2fdcf6caf74fd9c1552626ac31c78ba69e4e1df1e8346a15cbe4e
MD5 4bc4006cc68cc25c665b10cb6a99b2b4
BLAKE2b-256 7ab6a17d5297a894e74b628198867000cb9e743259b6175b41290a7de79b6c2b

See more details on using hashes here.

File details

Details for the file lalamo-0.6.1-py3-none-any.whl.

File metadata

  • Download URL: lalamo-0.6.1-py3-none-any.whl
  • Upload date:
  • Size: 129.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.26 {"installer":{"name":"uv","version":"0.9.26","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for lalamo-0.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 7c40f603f6dbbc7a1002cdee2abe3d1079ffc9a1c495ae6436c32eac97fbc371
MD5 a754807f724462a9215f9a175c5d1e2f
BLAKE2b-256 c8b825fc0e8aa38fbe6396b428c2e847ae566da877831e89080394b9029561ae

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page