然后在jupyter运行代码 from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda() response,history= model.chat(tokenizer,"你好...
NVIDIA ® TensorRT ™ 是一款用于高性能深度学习推理的 SDK,包含深度学习推理优化器和运行时,可为推理应用程序提供低延迟和高吞吐量。YOLOv10是清华大学研究人员近期提出的一种实时目标检测方法,通过消除NMS、优化模型架构和引入创新模块等策略,在保持高精度的同时显著降低了计算开销,为实时目标检测领域带来了...
# gradscalerscaler = torch.cuda.amp.GradScaler(enabled=args.enable_amp_mode)withtorch.cuda.amp.autocast(enabled=args.enable_amp_mode): # compute outputoutput = model(images)ifargs.enable_model_parallel:target = ts.distributed.gather(target, dim=0)loss = criterion(output, target) # compute ...
static void framebufferResizeCallback(GLFWwindow* window, int width, int height) { auto app = reinterpret_cast<HelloTriangleApplication*>(glfwGetWindowUserPointer(window)); app->framebufferResized = true; } 1. 2. 3. 4. 现在运行程序看看窗口大小改变的时候帧缓冲是否也跟随窗口正确调整了大小。 还...
The GPU Performance API (GPUPerfAPI, or GPA) is a powerful library which provides access to GPU Performance Counters. It can help analyze the performance and execution characteristics of applications using a Radeon™ GPU. This library is used byRadeon GPU Profileras well as several third-party...
mpv --no-config --gpu-api=vulkan --hwdec=auto Expected behavior play video Actual behavior Fail with error Resuming playback. This behavior can be disabled with --no-resume-playback. (+) Video --vid=1 (h264 3840x2160 60.000fps) (+) Audio --aid=1 'Track1' (aac 2ch 48000Hz) Can...
Netty 是一个异步基于事件驱动的高性能网络通信框架,可以看做是对 NIO 和 BIO 的封装,并提供了简单易用的 API、Handler... 京东云技术团队 128358围观2023-05-04 Hive 迁移参考方案及测试(下) 数据安全 聊完Hive的架构、工作原理,以及迁移方案,让我们一起来看下Hive的迁移测试。
model = AutoModelForCausalLM.from_pretrained(model_path).half().cuda() streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) instruction = """[INST] <<SYS>>\nYou are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being sa...
for(inttriangleBin=0;triangleBin<triangleBins;++triangleBin){autoentryPoint=L"Rasterize";// Change "Rasterize" into "Rasterize_k"refNames.emplace_back(std::format(L"{}_{}",entryPoint,triangleBin));// move into persistent allocation// Tell the linker to change the export name when linkingD3D...
并没有直接的去boxes里面删除框, 做了预分配, 给他们打上了标签, 合适的用emplace_back加上 */ // auto boxes = cpu_decode(ptr, nrows, ncols); vector<Box> cpu_decode(float *predict, int rows, int cols, float confidence_threshold = 0.25f, float nms_threshold = 0.45f) { // 创建一个...