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docs/compatibility.md

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+# Compatibility
+
+TorchMLX targets the common transformer operations used by GPT-2, Llama 3, Qwen 3, and GPT-OSS style implementations.
+
+Supported MLX operations include embeddings, linear layers, normalization building blocks, dropout, activations, causal attention, tensor shape operations, masks, top-k routing, and AdamW training through `Trainer`.
+
+MLX arrays remain native arrays. Torch-style tensor methods are installed on the native array type for the supported subset.
+
+Boolean expert routing and `unique` execute eagerly because their output shapes control Python flow.
+
+Set `TORCHMLX_BACKEND=torch` before import to use native PyTorch for unsupported programs. TorchMLX never changes backend during an operation.
+
+The referenced OpenArch model files contain source errors independent of TorchMLX, including invalid constructor calls and undefined attributes. Correct those errors before using either backend.