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导入"model = AutoModelForCausalLM.from_pretrained(
MODEL_PATH,
torch_dtype=TORCH_TYPE,
trust_remote_code=True,
low_cpu_mem_usage=True,
).eval()"
报"OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB (GPU 0; 23.69 GiB total capacity; 10.78 GiB already allocated; 10.94 MiB free; 10.79 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF"
Expected behavior / 期待表现
怎么指定它可以跑在多张GPU卡上
The text was updated successfully, but these errors were encountered:
System Info / 系統信息
linux系统
Who can help? / 谁可以帮助到您?
No response
Information / 问题信息
Reproduction / 复现过程
导入"model = AutoModelForCausalLM.from_pretrained(
MODEL_PATH,
torch_dtype=TORCH_TYPE,
trust_remote_code=True,
low_cpu_mem_usage=True,
).eval()"
报"OutOfMemoryError: CUDA out of memory. Tried to allocate 1002.00 MiB (GPU 0; 23.69 GiB total capacity; 10.78 GiB already allocated; 10.94 MiB free; 10.79 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF"
Expected behavior / 期待表现
怎么指定它可以跑在多张GPU卡上
The text was updated successfully, but these errors were encountered: