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https://github.com/huggingface/candle.git
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5635650d38
* Include the MLX gemm kernels. * Clippy lints. * Export the gemm_f32 kernel. * Add the f16/bf16 variants. * Add the initial dispatch code. * More plugging of the mlx kernels. * Add a currently broken test. * Tweaks. * Bugfix + get the tests to pass. * Enable the gemm bf16 tests. * Add some randomized tests. * Update candle-metal-kernels/src/lib.rs Co-authored-by: ivarflakstad <69173633+ivarflakstad@users.noreply.github.com> * More fixes. * More clippy fixes. --------- Co-authored-by: ivarflakstad <69173633+ivarflakstad@users.noreply.github.com>
27 lines
552 B
TOML
27 lines
552 B
TOML
[package]
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name = "candle-metal-kernels"
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version = "0.6.1"
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edition = "2021"
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description = "Metal kernels for Candle"
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repository = "https://github.com/huggingface/candle"
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keywords = ["blas", "tensor", "machine-learning"]
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categories = ["science"]
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license = "MIT OR Apache-2.0"
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[dependencies]
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metal = { version = "0.27.0", features = ["mps"] }
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once_cell = "1.18.0"
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thiserror = "1"
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tracing = "0.1.37"
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[dev-dependencies]
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half = { version = "2.3.1", features = [
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"num-traits",
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"use-intrinsics",
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"rand_distr",
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] }
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rand = "0.8.5"
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rand_distr = "0.4.3"
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