YOLOv12 is out; I made fine-tuning tutorial
instead of relying heavily on CNN-based architectures like its predecessors, YOLOv12 introduces “area attention” module, which strategically partitions the feature map to reduce the quadratic complexity of full self-attention.
notebook link: github.com/roboflow/noteb…
MLX uses nanobind (by @wenzeljakob) to bind C++ to Python. It's a critical piece of MLX infra and is why running Python code is nearly the same speed as running C++ directly.
Also makes it super easy to move arrays between frameworks. Examples:
RNNs/LSTMs struggle with tasks requiring long-range dependencies or handling sparse data due to their sequential construct. Transformer-based architectures like BERT excel in such cases, achieving higher accuracy with parallel processing.
#ArtificialIntelligence#nlp
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