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