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enable corda finetuning on xpu #2687

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Merged
merged 5 commits into from
Aug 5, 2025
Merged

enable corda finetuning on xpu #2687

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4c0cd7c
xpu enable
yao-matrix Jul 31, 2025
559a907
update README
yao-matrix Jul 31, 2025
52d9537
Merge branch 'huggingface:main' into corda-xpu
yao-matrix Jul 31, 2025
6d61dff
Update examples/corda_finetuning/README.md
yao-matrix Aug 4, 2025
8ef3665
Update examples/corda_finetuning/README.md
yao-matrix Aug 4, 2025
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12 changes: 9 additions & 3 deletions examples/corda_finetuning/README.md
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Expand Up @@ -150,7 +150,10 @@ corda_config = CordaConfig(
#### Knowledge-preserved adaptation mode

```bash
CUDA_VISIBLE_DEVICES=0 python -u preprocess.py --model_id="meta-llama/Llama-2-7b-hf" \
export CUDA_VISIBLE_DEVICES=0 # force to use device 0 of CUDA GPU
export ZE_AFFINITY_MASK=0 # force to use device 0 of Intel XPU

python -u preprocess.py --model_id="meta-llama/Llama-2-7b-hf" \
--r 128 --seed 233 \
--save_model --save_path {path_to_residual_model} \
--calib_dataset "nqopen"
Expand All @@ -165,7 +168,10 @@ Arguments:
#### Instruction-previewed adaptation mode

```bash
CUDA_VISIBLE_DEVICES=0 python -u preprocess.py --model_id="meta-llama/Llama-2-7b-hf" \
export CUDA_VISIBLE_DEVICES=0 # force to use device 0 of CUDA GPU
export ZE_AFFINITY_MASK=0 # force to use device 0 of Intel XPU

python -u preprocess.py --model_id="meta-llama/Llama-2-7b-hf" \
--r 128 --seed 233 \
--save_model --save_path {path_to_residual_model} \
--first_eigen --calib_dataset "MetaMATH"
Expand Down Expand Up @@ -248,4 +254,4 @@ Note that this conversion is not supported if `rslora` is used in combination wi
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
}
```
```
7 changes: 5 additions & 2 deletions examples/corda_finetuning/preprocess.py
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Expand Up @@ -38,8 +38,11 @@ def main(args):
# Setting random seed of numpy and torch
np.random.seed(args.seed)
torch.manual_seed(args.seed)
torch.cuda.manual_seed_all(args.seed)
torch.backends.cudnn.deterministic = True
if torch.cuda.is_available():
torch.cuda.manual_seed_all(args.seed)
elif torch.xpu.is_available():
torch.xpu.manual_seed_all(args.seed)
torch.use_deterministic_algorithms(True)

# Load model
model_id = args.model_id
Expand Down
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