max GPU memory usage for Ultra 5 125H / 155H Subscribe More actions peter-sk Beginner 06-11-2024 02:02 PM 523 Views Hi, does anyone know how much of the RAM can be used for the GPU/NPU in the Ultra 5 series? I have see some reports of up to 48 GB in a...
Question #1 -- Is there a way to configure the GPU for the default output resolution? Question #2 -- Since our display is very small, how can I reduce the GPU driver memory consumption? (In 3.0.35 this was easy... but in 3.10.53, I can't find where to do this). R...
state["device"]): max_vram_mb = int(torch.cuda.max_memory_allocated(args.state["device"]) / (1024 * 1024)) logger.debug(f"GPU Max Memory Allocated {max_vram_mb}MB") if __name__ == "__main__": main() 0 comments on commit 0074490 Please sign in to comment. ...
you mention the gpu memory usage, but what about gpu usage itself? you can use gpu-z to monitor its usage, watching gpu load %. if its near max it is the bottleneck, probably from fx like MB denoiser. if its usage is low, its probably AE and/or the fx/...
ValueError: The model's max seq len (32768) is larger than the maximum number of tokens that can be stored in KV cache (26064). Try increasing gpu_memory_utilization or decreasing max_model_len when initializing the engine. Mistral-7B-v0.1 aklakl commented Jan 14, 2024 Same exception wi...
最快解決辦法, 是調低batch_size , 例如設為32. Try reducing your batch_size (ex. 32). This can happen because your GPU memory can’t hold all your images for a single epoch.
importtorch torch.backends.cuda.max_split_size_mb=1024# 设置每个块的最大尺寸为1GB 如果使用多GPU训练时,可以尝试将数据并行度调小,即减少每个GPU上的batch size。 如果以上方法都没有解决问题,则需要考虑使用更高配置的GPU或者增加机器内存来缓解该问题。
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max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF 这是报显卡内存不足。 二、报错原因 直接原因:机器显存太小,穷; 根本原因:给模型的prompt太长。 prompt是由history与query进行拼接得到,在chat()方法中,将每一轮历史问答记录old_query、response与...
Apple unveils M2 chipset with 18% faster CPU, 35% faster GPU compared to the M1 Apple's M1 Pro and M1 Max SoCs are official with much improved performance over the M1 Apple announces M1 Ultra with 20-core CPU and 64-core GPU