Maintained fork with PyTorch bindings and macOS 15 support

Hey! I've been using metal-flash-attention for a PyTorch training project on Apple Silicon and made some additions: ## Fork: [imperatormk/metal-flash-attention](https://github.com/imperatormk/metal-flash-attention) **Changes:** - ✅ Causal masking support (for autoregressive models) - ✅ macOS 15 (Sequoia) compatibility fixes - ✅ Tested with PyTorch MPS backend ## PyTorch Bindings: [imperatormk/mps-flash-attention](https://github.com/imperatormk/mps-flash-attention) Drop-in Flash Attention for PyTorch on Apple Silicon: - O(N) memory instead of O(N²) - 2-5x faster than PyTorch SDPA - Full backward pass for training - Pre-compiled kernels for zero cold start ```python from mps_flash_attn import flash_attention out = flash_attention(q, k, v, is_causal=True) ``` If you're interested in merging any of these changes upstream, happy to open a PR! Thanks for the original library - it's been super helpful for training on M1/M3 Macs.