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dbb23fbfa8
Packing of asymmetric quantization is broken, all (q)zeros values of `0` get reset to `1`, resulting in a loss of accuracy. So instead use symmetric quantization. To be able to distinguish models with symmetric and asymmetric quantization, a new config tensor `gptq_sym` is added. If this tensor is not present, we assume `sym=False`. |
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| .. | ||
| attention | ||
| awq | ||
| gptq | ||
| __init__.py | ||
| bnb.py | ||
| conv.py | ||
| eetq.py | ||
| exl2.py | ||
| fp8.py | ||
| layernorm.py | ||
| linear.py | ||
| lora.py | ||
| marlin.py | ||
| medusa.py | ||
| mlp.py | ||
| rotary.py | ||
| speculative.py | ||
| tensor_parallel.py | ||