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Use weights_only for load #5

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Merged
merged 1 commit into from
Nov 30, 2023
Merged

Use weights_only for load #5

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2 changes: 1 addition & 1 deletion generate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -219,7 +219,7 @@ def _load_model(checkpoint_path, device, precision, use_tp):
simple_quantizer = WeightOnlyInt4QuantHandler(model, groupsize)
model = simple_quantizer.convert_for_runtime()

checkpoint = torch.load(str(checkpoint_path), mmap=True)
checkpoint = torch.load(str(checkpoint_path), mmap=True, weights_only=True)
model.load_state_dict(checkpoint, assign=True)

if use_tp:
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2 changes: 1 addition & 1 deletion quantize.py
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Expand Up @@ -540,7 +540,7 @@ def quantize(
with torch.device('meta'):
model = Transformer.from_name(checkpoint_path.parent.name)

checkpoint = torch.load(str(checkpoint_path), mmap=True)
checkpoint = torch.load(str(checkpoint_path), mmap=True, weights_only=True)
model.load_state_dict(checkpoint, assign=True)
model = model.to(dtype=precision, device=device)

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2 changes: 1 addition & 1 deletion scripts/convert_hf_checkpoint.py
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Expand Up @@ -64,7 +64,7 @@ def permute(w, n_head):

merged_result = {}
for file in sorted(bin_files):
state_dict = torch.load(str(file), map_location="cpu", mmap=True)
state_dict = torch.load(str(file), map_location="cpu", mmap=True, weights_only=True)
merged_result.update(state_dict)
final_result = {}
for key, value in merged_result.items():
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