通过上述步骤,您应该能够解决遇到的“ValueError: bf16 mixed precision requires PyTorch >= 1.10 and a supported device”错误。如果问题仍然存在,请提供更多的系统信息,以便进一步诊断问题。
https://github.com/Lightning-AI/lightning/blob/b441b3ea2112ba8def3e7f66fd30fcfbabf92f00/src/lightning/pytorch/plugins/precision/fsdp.py#L102-L116 Excerpt from the FSDP MixedPrecisiondocs: "This specifies the dtype for model parameters, inputs [...], and therefore the dtype for computation...
70 + fp16 = True # turn on mixed precision training with apex 70 71 ) 71 72 72 73 trainer.train() denoising_diffusion_pytorch/denoising_diffusion_pytorch.py +46-10 Original file line numberDiff line numberDiff line change @@ -16,6 +16,12 @@ 16 16 from tqdm import t...
Latter, I found the issue had been solved in the latest pytorch 2.5.0. So if you encounter the same problem, try to upgrade your pytorch environment.
This is on top of Hugging Face transformers with Pytorch backend, which natively requires a number of expensive GPU resources and takes significant time. By constract, BigDL here provides a CPU optimization to accelerate the lora finetuning of Llama 7b, in the power of mixed-precision and ...
This is on top of Hugging Face transformers with Pytorch backend, which natively requires a number of expensive GPU resources and takes significant time. By constract, BigDL here provides a CPU optimization to accelerate the lora finetuning of Llama 7b, in the power of mixed-precision and ...
mixed_audio: The mixed audio to separate in_sr: The sample rate of the input audio steps: The number of diffusion steps to run conditioning: The conditioning to use for source separation conditioning_tensors: Pre-computed conditioning tensors to use for source separation. If provided, conditioni...
This is on top of Hugging Face transformers with Pytorch backend, which natively requires a number of expensive GPU resources and takes significant time. By constract, BigDL here provides a CPU optimization to accelerate the lora finetuning of Llama 7b, in the power of mixed-precision and ...