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-0.5.8.tar.gz (88.9 kB view details)

Uploaded Source

Built Distribution

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

lalamo-0.5.8-py3-none-any.whl (117.6 kB view details)

Uploaded Python 3

File details

Details for the file lalamo-0.5.8.tar.gz.

File metadata

  • Download URL: lalamo-0.5.8.tar.gz
  • Upload date:
  • Size: 88.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.16 {"installer":{"name":"uv","version":"0.9.16","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-0.5.8.tar.gz
Algorithm Hash digest
SHA256 3b2d26a639cfb1c91066268b1801eed551ca9ddebed0ee64b25cec0ff938149a
MD5 be08668513f3bdfaa27b0640393073a6
BLAKE2b-256 151ad2a3c78f032b0617ba4d68e0f4e154d74a729d693f09a0a09d15446a1e32

See more details on using hashes here.

File details

Details for the file lalamo-0.5.8-py3-none-any.whl.

File metadata

  • Download URL: lalamo-0.5.8-py3-none-any.whl
  • Upload date:
  • Size: 117.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.16 {"installer":{"name":"uv","version":"0.9.16","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-0.5.8-py3-none-any.whl
Algorithm Hash digest
SHA256 7a2b51bb69c08e50f5d949066d2051ac79ebbd4721b2b27479c35ca271fbefb4
MD5 833eb3f1e521667fdb8c2ec1d5e7df80
BLAKE2b-256 483eb488006b1eadce043f45f12af369744137841e670bc3e59cc9be01e3a4d9

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