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-0.5.2.tar.gz (78.2 kB view details)

Uploaded Source

Built Distribution

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

lalamo-0.5.2-py3-none-any.whl (104.1 kB view details)

Uploaded Python 3

File details

Details for the file lalamo-0.5.2.tar.gz.

File metadata

  • Download URL: lalamo-0.5.2.tar.gz
  • Upload date:
  • Size: 78.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.9 {"installer":{"name":"uv","version":"0.9.9"},"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-0.5.2.tar.gz
Algorithm Hash digest
SHA256 4e16de9b05c7fa560fa8e90a90b03b6a675f7c7eb7136f63f1901d49f3d90e70
MD5 c480cf64b8569fd09d4ffe853285c5bd
BLAKE2b-256 0514d3abc94b036b555db1f6e5e679dff4be49148931e2c559078262dd228a9a

See more details on using hashes here.

File details

Details for the file lalamo-0.5.2-py3-none-any.whl.

File metadata

  • Download URL: lalamo-0.5.2-py3-none-any.whl
  • Upload date:
  • Size: 104.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.9 {"installer":{"name":"uv","version":"0.9.9"},"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-0.5.2-py3-none-any.whl
Algorithm Hash digest
SHA256 fe3da10963db71ab15a6826bd62f45a044ce06346706a079878ace562227d2d6
MD5 5da2a902f690024de75ee25602b68037
BLAKE2b-256 c80b182711ba374a46a46bd2c5a3a0bbd248682a1a09886e50802f677bae6d80

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