which is a transformer-based neural network language model that has been
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When shape similarity lies: size-ratio artifacts in confusable detection Confusable detection pipelines normalise characters to a fixed canvas before measuring similarity. This hides natural size differences. We re-rendered 2,203 scored pairs (TR39 baseline + novel discoveries) at their original sizes and found 254 with width or height ratios above 2x.
The API deals exclusively with bytes (Uint8Array). Strings are UTF-8 encoded automatically. There's no "value stream" vs "byte stream" dichotomy. If you want to stream arbitrary JavaScript values, use async iterables directly. While the API uses Uint8Array, it treats chunks as opaque. There is no partial consumption, no BYOB patterns, no byte-level operations within the streaming machinery itself. Chunks go in, chunks come out, unchanged unless a transform explicitly modifies them.