mirror of https://github.com/hpcaitech/ColossalAI
27 lines
670 B
Python
27 lines
670 B
Python
import torch
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import torch.nn as nn
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from .model_utils import find_layers
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from .quant import make_quant
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def load_quant(model: nn.Module, checkpoint: str, wbits: int, groupsize: int):
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model = model.eval()
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layers = find_layers(model)
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# ignore lm head
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layers = find_layers(model)
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for name in ['lm_head']:
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if name in layers:
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del layers[name]
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make_quant(model, layers, wbits, groupsize)
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if checkpoint.endswith('.safetensors'):
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from safetensors.torch import load_file as safe_load
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model.load_state_dict(safe_load(checkpoint))
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else:
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model.load_state_dict(torch.load(checkpoint))
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return model
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