针对你遇到的“failed to load cpm_kernels: could not find module 'nvcuda.dll'”错误,这通常意味着系统无法找到或加载CUDA的DLL文件。下面是一些可能的解决步骤: 确认CUDA安装: 首先,确认你的系统上是否安装了CUDA。如果没有安装,你需要从NVIDIA官方网站下载并安装适合你系统的CUDA版本。 安装完成后,检查CUDA的...
Requriements.txt文档里列出了ChatGLM使用的主要开源组件的清单与版本号,其核心是transformers,需要版本4.27.1,实际上要求没有这么严格,略低一点也没太大问题,不过安全起见还是用相同的版本为好。Icetk是做Token处理的,cpm_kernels是中文处理模型与cuda的核心调用,protobuf是结构化数据存储的。Gradio是用于利用Python快速...
cpm_kernels这个库中有一个lookup_dll函数,这个函数会查找系统环境变量 PATH 中指定前缀的 DLL 文件并返回找到的第一个 DLL 文件的完整路径。将这个函数改为 def lookup_dll(prefix): paths = os.environ.get("PATH", "").split(os.pathsep) for path in paths: ...
Adding or changing kernels Each custom kernel needs a schema and one or more implementations to be registered with PyTorch. Make sure custom ops are registered following PyTorch guidelines: Custom C++ and CUDA Operators and The Custom Operators Manual Custom operations that return Tensors require meta...
Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP) Vulkan and SYCL backend support CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacitySince its inception, the project has improved significantly thanks to many contributions. It...
Optimized CUDA kernels, including integration with FlashAttention and FlashInfer. Speculative decoding Chunked prefill Performance benchmark: We include aperformance benchmarkthat compares the performance of vLLM against other LLM serving engines (TensorRT-LLM,text-generation-inferenceandlmdeploy). ...
/usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.7.0 HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 24 On-line CPU(s) list: 0...
Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP) Vulkan, SYCL, and (partial) OpenCL backend support CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity Since its inception, the project has improved significantly thanks to...
ROCm 5.7 pip install auto-gptq --no-build-isolation --extra-index-url https://huggingface.github.io/autogptq-index/whl/rocm573/ 2.2.1+rocm5.7 Intel® Gaudi® 2 AI accelerator BUILD_CUDA_EXT=0 pip install auto-gptq --no-build-isolation 2.3.1+Intel Gaudi 1.17Auto...
[2024/02] AMD ROCm support through ExLlamaV2 kernels. [2024/01] Export to GGUF, ExLlamaV2 kernels, 60% faster context processing. [2023/12] Mixtral, LLaVa, QWen, Baichuan model support. [2023/11] AutoAWQ inference has been integrated into 🤗 transformers. Now includes CUDA 12.1 wheel...