Feature Extraction
MLX
English
hrr
vsa
holographic-reduced-representations
tokenizer
morphemes
compositional
Instructions to use thebasedcapital/morph-hrr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use thebasedcapital/morph-hrr with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir morph-hrr thebasedcapital/morph-hrr
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 873 Bytes
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requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "morph-hrr"
version = "0.1.1"
description = "Compositional HRR morpheme tokenizer/embeddings: circular-convolution prefix (x) root (x) suffix, for Apple MLX."
readme = "README.md"
requires-python = ">=3.11"
license = "MIT"
authors = [{ name = "BB Claude" }]
keywords = ["hrr", "vsa", "hyperdimensional", "tokenizer", "morphology", "mlx", "embeddings", "circular-convolution"]
classifiers = [
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: MacOS",
]
dependencies = ["mlx", "numpy"]
[project.optional-dependencies]
test = ["pytest"]
[project.urls]
Repository = "https://huggingface.co/<user>/morph-hrr"
[tool.hatch.build.targets.wheel]
packages = ["src/morph_hrr"]
[tool.pytest.ini_options]
pythonpath = ["src"]
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