check_language(CUDA)if(CMAKE_CUDA_COMPILER) enable_language(CUDA) set(CMAKE_CUDA_STANDARD14) set(CMAKE_CUDA_STANDARD_REQUIREDON) add_compile_definitions(USE_CUDA)else(CMAKE_CUDA_COMPILER) message(STATUS"No CUDA support") remove_definitions(USE_CUDA) endif(CMAKE_CUDA_COMPILER) Run Code Online...
Without this change even if we have added "-allow-unsupported-compiler" to CMAKE_CUDA_FLAGS_INIT, the check will still fail. Sorry I don't know why.
# Option1: open-source modelfromselfcheckgpt.modeling_selfcheckimportSelfCheckLLMPromptdevice=torch.device("cuda"iftorch.cuda.is_available()else"cpu")llm_model="mistralai/Mistral-7B-Instruct-v0.2"selfcheck_prompt=SelfCheckLLMPrompt(llm_model,device)# Option2: API access# (currently only support...
./decent.sh:行 62: 6088 已放弃 (核心已转储) decent quantize -model ${model_dir}/float.prototxt -weights ${model_dir}/float.caffemodel -output_dir ${output_dir} -method 1 My environment is Ubuntu16.04\+cuda9.0\+cudnn7.05,how can I deal with it...
frommagmaimportMagmafrommagma.image_inputimportImageInputmodel=Magma.from_checkpoint(config_path="configs/MAGMA_v1.yml",checkpoint_path="./mp_rank_00_model_states.pt",device='cuda:0')inputs=[## supports urls and path/to/imageImageInput('https://www.art-prints-on-demand.com/kunst/thomas_co...
C++ implementation of LSTM (Long Short Term Memory), in Kaldi's nnet1 framework. Used for automatic speech recognition, possibly language modeling etc, the training can be switched between CPU and GPU(CUDA). This repo is now merged into official Kaldi c