针对你遇到的ValueError: requested float16 compute type, but the target device or backend错误,以下是一些可能的解决步骤和解释: 1. 错误类型识别 该错误是一个ValueError,表明你尝试使用的参数值不符合函数或方法的预期。在这个案例中,错误提示你请求了float16计算类型,但目标设备或后端不支持
type=precision) File "D:\tools\ai\GPT-SoVITS-beta0217\runtime\lib\site-packages\faster_whisper\transcribe.py", line 130, in __init__ self.model = ctranslate2.models.Whisper( ValueError: Requested float16 compute type, but the target device or backend do not support efficient float16 ...
ValueError: Bfloat16 is only supported on GPUs with compute capability of at least 8.0. Your NVIDIA GeForce RTX 2080 Ti GPU has compute capability 7.5. ValueError: Bfloat16 is only supported on GPUs with compute capability of at least 8.0. Your NVIDIA GeForce RTX 2080 Ti GPU has compute ca...
ValueError: Bfloat16 is only supported on GPUs with compute capability of at least 8.0. Your Tesla T4 GPU has compute capability 7.5. Try to build vLLM from sources (mainbranch) and use the--dtype floatparameter. See also1ac4ccf #1144...
请提出你的问题 位置:applications/text_classification/multi_class 进行的是模型裁剪操作 环境: paddle-bfloat 0.1.7 paddle2onnx 1.1.0 paddlefsl 1.1.0 paddlenlp 2.8.0 paddleocr 2.7.0.3 paddlepaddle 2.6.1 paddleslim 2.6.0 scikit-learn 1.4.2 裁剪操作时候的命令:
Since vLLM 0.2.5, we can't even run llama-2 70B 4bit AWQ on 4*A10G anymore, have to use old vLLM. Similar problems even trying to be two 7b models on 80B A100. For small models, like 7b with 4k tokens, vLLM fails for "cache blocks" even ...
The new graph will be + pruned so subgraphs that are not necessary to compute the requested + outputs are removed. + @param session The TensorFlow session to be frozen. + @param keep_var_names A list of variable names that should not be frozen, + or None to freeze all the variables ...