Tag: Transformer
-
Mamba-2 vs Mamba vs Transformer: Long Range Arena Results
Mamba-2 claims 8x faster training than Mamba while matching accuracy on 16K-token tasks. Here's what the Long Range Arena benchmark reveals.
-
Self-Attention from Scratch: NumPy vs PyTorch Implementation
Build self-attention from scratch using NumPy and PyTorch. Compare implementations, understand matrix operations, and master transformer architecture.
-
RNN to Transformer NMT: PyTorch Migration with 2.8x BLEU Gain
Stuck at BLEU 18 with GRU seq2seq? Here's the PyTorch code that hit BLEU 51 after migrating to Transformerโplus the causal mask bug that wasted 3 days.
-
Transformer vs CNN-LSTM: CWRU Bearing 96% vs 92% Accuracy
Compare Transformer vs CNN-LSTM for bearing fault detection on CWRU dataset. Discover which architecture achieves 96% accuracy and why it wins.
-
LSTM vs Transformer: S&P 500 1-Year Benchmark Results
LSTM vs Transformer showdown: 1-year S&P 500 predictions reveal surprising accuracy gaps. Which architecture wins for financial forecasting?
-
LSTM vs GRU vs Transformer RUL: NASA CMAPSS Memory Test
Compare LSTM, GRU, and Transformer models for RUL prediction on NASA CMAPSS dataset. Which architecture wins the turbofan memory test?
-
LSTM Attention vs Self-Attention: How Bahdanau Evolved
Bahdanau's 2014 attention fixed seq2seq bottlenecks but kept sequential encoders. How three key problems led to self-attention and 3x speedups.
-
DETR vs Faster R-CNN: End-to-End Detection Hits 42 AP
Compare DETR vs Faster R-CNN object detection: how Transformers eliminate anchors and NMS to match 42 AP while simplifying the detection pipeline.