在解决“valueerror: tried to use fp16 but it is not supported on cpu”这个错误时,我们可以按照您提供的提示来逐步分析和解决问题。以下是详细的回答: 1. 确认错误信息的含义 这个错误信息表明您的代码尝试在CPU上使用半精度浮点数(fp16),但当前的CPU硬件或环境配置不支持这种操作。fp16主要用于加速深度学习...
报错: 代码语言:javascript 复制 PSD:\>whisper.exe.\dz.wav--language en--model mediumC:\xxPython310\lib\site-packages\whisper\transcribe.py:114:UserWarning:FP16is not supported onCPU;usingFP32instead warnings.warn("FP16 is not supported on CPU; using FP32 instead") 这个报错说的是whisper要使...
C:\Users\DIMIO\AppData\Local\Programs\Python\Python39\lib\site-packages\whisper\transcribe.py:114: UserWarning: FP16 is not supported on CPU; using FP32 instead I added --fp16 False Still have a problem, do not know how to modify? whisper h:\M.mp4 --model tiny --fp16 False E:\P...
PS D:\> whisper.exe .\dz.wav --language en --model medium C:\xxPython310\lib\site-packages\whisper\transcribe.py:114: UserWarning: FP16 is not supported on CPU; using FP32 instead warnings.warn("FP16 is not supported on CPU; using FP32 instead") 这个报错说的是whisper要使用cpu,而...
whisper 报错 FP16 is not supported on CPU; using FP32 instead 博客园 报错内容:P16 is not supported on CPU; using FP32 instead 解决办法:在最后加上-- fp16 False whisper git地址:https://github.com/openai/whisper?tab=readme-ov-file
whisper 报错 FP16 is not supported on CPU; using FP32 instead 博客园,报错内容:P16isnotsupportedonCPU;usingFP32instead解决办法:在最后加上--fp16Falsewhispergit地址:
I use custom_finetune.sh and no other redundant parameter settings have been changed. encountered a problem that is " raise ValueError("Type fp16 is not supported.")ValueError: Type fp16 is not supported." All installation follows README...
But in this case there are supported CPUs with AVX512F, but without AVX512-FP16 - and yet no AVX512-FP16 macro at all. It’s not surprising on itself since AVX512-FP16 support was added to MSVC quite recently (VS 17.2+/MSVC 19.31+, 2022). Yet it still is a pretty b...
Don’t know whether it’s supported on NVIDIA’s ARM platforms, but it definitely seems worth a try.Robert_Crovella 2015 年10 月 10 日 14:41 7 LukeCuda: i would rather not try to put my floats on the device and then convert them, because the whole point of half is to save ...
"Exporting to ONNX in fp16 is not supported. Please export in fp32, i.e. disable AMP." How do I convert to int8+fp16? Or if not possible, how to I get the performance benefits without doing that? Environment I'm using nvcr.io/nvidia/tensorrt:22.02-py3 with the latest torch and...