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ToRSh is a pure-Rust, PyTorch-compatible deep-learning framework with native tensor sharding. 0.1.2 lands real AVX2/NEON SIMD for f32 ops and activations, a true zero-copy buffer pool (100% heap-block reduction on hot loops), and SIMD + parallel enabled by default.
ToRSh is a PyTorch-compatible deep-learning framework in pure Rust with native tensor sharding. The 0.1.1 release hardens the 33-crate workspace onto consistent, published crates.io dependencies and adds the new torsh-convert model-converter CLI.