Instructions to use Motif-Technologies/optimizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use Motif-Technologies/optimizer with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("Motif-Technologies/optimizer") - Notebooks
- Google Colab
- Kaggle
Muon Optimizer Test
This directory contains a test script for the Muon optimizer.
Prerequisites
GPU Requirement
- All tests require 8 GPUs by default.
- If you have fewer GPUs available:
- Modify the parallelism configurations in
test_muon.py.
- Modify the parallelism configurations in
Model Access
- The tests require access to the private model repository:
Motif-Technologies/Motif-2.6B-4layer-randomon Hugging Face.
- Set your Hugging Face token via the environment variable
HF_TOKEN. - If you don’t have access, please contact the maintainer.
- The tests require access to the private model repository:
Using a Different Model (Optional)
- You may modify the test to use a different model by:
- Updating the model name in
conftest.py::inputs. - Adjusting the tensor parallel rules in
utils.py::_apply_tp.
- Updating the model name in
- You may modify the test to use a different model by:
Usage
- To execute the test with 8 GPUs, simply run:
./run_test.sh
- To check the other available options, you can use:
pytest --help
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Custom options:
--measure-perf Measure execution time and peak memory usage during optimizer step.
--do-profile Enable profiling during tests.
--skip-verify Skip verification of optimizer step correctness with sequential implementation.
This can be useful when GPU memory is limited.
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