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| -rw-r--r-- | README.md | 6 |
1 files changed, 3 insertions, 3 deletions
@@ -23,12 +23,12 @@ Resources: 1. Comment out torch.nn.Linear: ``#linear = torch.nn.Linear(...)`` 2. Add bnb 8-bit linear light module: ``linear = bnb.nn.Linear8bitLt(...)`` (base arguments stay the same) 3. There are two modes: - - Mixed 8-bit training with 16-bit main weights. Pass the argument ``use_fp16_weights=True`` (default) - - Int8 inference. Pass the argument ``use_fp16_weights=False`` + - Mixed 8-bit training with 16-bit main weights. Pass the argument ``has_fp16_weights=True`` (default) + - Int8 inference. Pass the argument ``has_fp16_weights=False`` 4. To use the full LLM.int8() method, use the ``threshold=k`` argument. We recommend ``k=6.0``. ```python # LLM.int8() -linear = bnb.nn.Linear8bitLt(dim1, dim2, bias=True, use_fp16_weights=False, threshold=6.0) +linear = bnb.nn.Linear8bitLt(dim1, dim2, bias=True, has_fp16_weights=False, threshold=6.0) # inputs need to be fp16 out = linear(x.to(torch.float16)) ``` |