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ml_dtypes

ml_dtypes is a stand-alone implementation of several NumPy dtype extensions usedin machine learning libraries, including:bfloat16: an alternative to the standard float16 formatfloat8_*: several experimental 8-bit floating point representations including:float8_e4m3b11fnuzfloat8_e4m3fnfloat8_e4m3fnuzfloat8_e5m2float8_e5m2fnuz

https://github.com/jax-ml/ml_dtypes

Available modules

The overview below shows which ml_dtypes installations are available per target architecture in EESSI, ordered based on software version (new to old).

To start using ml_dtypes, load one of these modules using a module load command like:

module load ml_dtypes/0.3.2-gfbf-2023a

(This data was automatically generated on Fri, 06 Feb 2026 at 13:12:13 UTC)

aarch64/generic aarch64/a64fx aarch64/neoverse_n1 aarch64/neoverse_v1 aarch64/nvidia/grace x86_64/generic x86_64/amd/zen2 x86_64/amd/zen3 x86_64/amd/zen4 x86_64/intel/cascadelake x86_64/intel/haswell x86_64/intel/icelake x86_64/intel/sapphirerapids x86_64/intel/skylake_avx512
ml_dtypes/0.3.2-gfbf-2023a x x x x x x x x x x x x x x

ml_dtypes/0.3.2-gfbf-2023a

This is a list of extensions included in the module:

etils-1.6.0, ml_dtypes-0.3.2, opt_einsum-3.3.0