feat: add fused QKV for other bitnet models #6
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Blaizzy
reviewed
Jun 15, 2025
Owner
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I thought about making it configurable. But I think we can just keep it fused for bitnet because of the increased performance.
Author
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Makes sense, let's put it to True always then
Blaizzy
reviewed
Jun 15, 2025
mlx_lm/quant/utils.py
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| def apply_hf_quantization(model, config): | ||
| def apply_hf_quantization(model, config, weights): |
Owner
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Please ensure the tests bitnet_llama tests are passing. Because I use this function there
Blaizzy
requested changes
Jun 15, 2025
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Blaizzy
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This is awesome!
I just have a couple nits.
Blaizzy
reviewed
Jun 15, 2025
mlx_lm/models/bitlinear_layers.py
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| print(f"{name:<16}: {dt*1e3:.1f} ms | {(bs*sl)/dt:,.0f} tok/s") | ||
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| class BitFusedAttention(nn.Module): |
Owner
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Let's also import this module on bitnet.py to avoid having duplicates.
Author
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Addressed all comments ! LMK wdyt |
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@Blaizzy