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convert : refactor vocab selection logic (#6355)
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@@ -106,12 +106,12 @@ def main():
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tensor_map = gguf.get_tensor_name_map(arch, block_count)
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print(tensor_map)
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for name in tensors.keys():
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data = tensors[name]
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data_torch = tensors[name]
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if name.endswith(".self_attention.rotary_emb.inv_freq"):
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continue
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old_dtype = data.dtype
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old_dtype = data_torch.dtype
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# TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?)
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data = data.to(torch.float32).squeeze().numpy()
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data = data_torch.to(torch.float32).squeeze().numpy()
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new_name = tensor_map.get_name(name, try_suffixes = (".weight", ".bias"))
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if new_name is None:
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print("Can not map tensor '" + name + "'")
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