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Tien Dung
tiendung
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SparseLLM/BlockFFN-3B-SFT
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10 days ago
turboderp/ERNIE-4.5-300B-A47B-PT-exl3
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14 days ago
I played around with the new RXTX paper (XX^T) and was able to train nanogpt with 4x4 RXTX matmuls in both attention layer and optimizer🤕 It just works (well I had to add some guardrails) but still saves 5% of memory usage: The Patch: - Computes attention scores with a 4x4 blockwise RXTX matmuls (no pytorch dot prod) - Handles arbitrary sequence lengths by padding to the nearest multiple of 4. - An RXTX variant of shampoo with params reshaped into 4x4 blocks during each optimizer step. - Uses 5% less ops Code: https://github.com/Jaykef/ai-algorithms/blob/main/nanogpt-rxtx.ipynb Paper: https://arxiv.org/pdf/2505.09814
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SparseLLM/BlockFFN-3B-SFT
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turboderp/ERNIE-4.5-300B-A47B-PT-exl3
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mistralai/Magistral-Small-2506
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KhangHatto/alpha
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HPLT/hplt_bert_base_2_0_vie-Latn
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inclusionAI/Ling-lite
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