Cuda extension not installed gptq 1. WARNING: Skipping auto-gptq as it is not installed. 1-GPTQ" # To use a different branch, change revision With transformers and auto_gptq, the logs suggest CUDA extension not installed. ` 2. 2 这个报错一般是autogptq的版本跟torch的cuda不匹配了，建议找个对应torch和cuda版本的autogptq安装下试试。对的，我原来的auto_gptq版本和我的pytorch不匹配，之后从auto_gptq官方源码开始安装的，顺利安装好了，和我pytorch 2. I used the prebuilt wheel: auto_gptq-0. 5-72B-Instruct-GPTQ-Int8 and Qwen2-72B-Instruct-GPTQ-Int8 What is the scenario where the problem happened? transformers Is this a known issue? I h Installation. py Compressing all models from the OPT and BLOOM families to 2/3/4 bits, including weight grouping: opt. dev torch. auto-gptq v0. You can try: If that doesn't work, please report on the AutoGPTQ Github. The model does run and produce output though, so I'm not sure if there's actually an issue here. The current release includes the following features: An efficient implementation of the GPTQ algorithm: gptq. You signed in with another tab or window. 04 from the Microsoft Store, then open it and follow the installation process for linux instead. You signed out in another tab or window. 4. You are using pytorch without CUDA support. Tests can be run with: pytest tests/ -s FAQ Which kernel is used by default? AutoGPTQ defaults to using exllamav2 int4*fp16 kernel for matrix multiplication. gz (62 kB Does cuda 12. Warnings regarding TypedStorage : `UserWarning: TypedStorage is deprecated. Released: Mar 22, 2023. dev0+cu118。谢谢！ Describe the bug Since auto-gptq==0. It will be removed in the future and UntypedStorage will be import autogptq_cuda_64 _autogptq_cuda_available = True except ImportError: logger. See 文章浏览阅读6k次，点赞3次，收藏12次。我刚开始直接pip install auto-gptq，产生了一系列的问题。本地是CUDA11. Follow its installation guide to install a pre-built wheel or try installing auto_gptq from source. In 0. I'm not using docker, just a local dev PC with Currently, for each NNabla CUDA extension package, it may be not compatible with some specific GPUs. I get this warning, and the model is definetely not using the GPU: WARNING:auto_gptq. py文件后，提示CUDA extension not installed. Install the toolkit and try I have a warning that some CUDA extension is not installed, though localGPT works fine. nn_modules. The issue appears to be that the GPTQ/CUDA setup only happens if there is no GPTQ folder inside repositiories, so if you're pip install gptq Copy PIP instructions. qlinear. 2 with cuda 12 But your log says the mismatch is between your cuda-toolkit (12. Latest version. conda install -c conda-forge cudatoolkit-dev; 1. Most of the time I get "CUDA Extension not installed. 3. 3k次，点赞16次，收藏15次。通常是由于没有正确安装 CUDA 支持的深度学习框架，或者系统的 CUDA 环境配置有问题。通过重新安装支持 CUDA 的版本、检查 CUDA 和 cuDNN 安装、确保 GPU 驱动正常运行，应该能解决这个问题。_cuda This repository contains the code for the ICLR 2023 paper GPTQ: Accurate Post-training Compression for Generative Pretrained Transformers. 0. 文章浏览阅读1. 2 work with the latest torch version? I have cude 12. Yes, "CUDA extension not installed" is exactly the problem. py, Hi there, I did a fresh installation of Ubuntu and tried running some examples from TheBloke's models. Now I can run models if I use use_triton=True, but it's worth turning it off as "CUDA extension not installed" or "name autogptq_cuda_256 not defined" errors pop up. " when running the Python script. and installing PyTorch with CUDA is Install Ubuntu 22. " in ooba I'm getting error: Upload images, audio, and videos by dragging in the text input, pasting, or clicking here. 1匹配的是auto_gptq==0. Hopefully fairly soon there will be pre-built binaries for AutoGPTQ and it won't be necessary to compile from source, but currently it is. `CUDA SETUP: Detected CUDA version 117` however later `CUDA extension not installed. For example, you can check GPU with device_id 0 by: How do I install CUDA?¶ NNabla CUDA extension requires both CUDA toolkit and cuDNN library I adapted the following bat to automate the install GPTQ for LLaMa. CUDA kernels for auto_gptq are not installed, this will result in very slow How to solve this warning? CUDA extension not installed. Discussion mvetter. CUDA and for the installation of auto-gptq, we advise you to install from source (git clone the repo and run pip install -e . You switched accounts on another tab or window. modeling import I tryed to install the binding on a linux ubuntu pc with a GPU, but every thing works perfectly until I try to run the model. You disabled CUDA extensions compilation by setting BUILD_CUDA_EXT=0 when install auto_gptq from source. cuda. I want to adapt and run the GPTQ model in the environment of Cuda 10. whl I am using the localGPT open source project to run the mistral 7b model on my RTX 3090 24gb GPU. 6k次，点赞4次，收藏2次。引用auto_gptq时报CUDA extension not installed的提示。2、安装bitsandbytes。3、从源码安装gptq。_cuda extension not installed. 0 breaks AutoGPTQ completely. 7) Unfortunately, only now I fully realized that the problem is still in the cuda extension. If you do, just make sure that the cuda installed in your windows and linux are the same version, otherwise you'll run into errors. 解决方案（以下解决方案的前提是torch torchvision torchaudio都装好cu118版本了）： 1、下载官方源码： git clone To use exllama_kernels to further speedup inference, you can re-install auto_gptq from source. 1+cu121: ROCm 5. Twice actually. collect_env) Sammeln von Umgebungsinformationen PyTorch Version: 2. 2 it would still run, just really slowly (1 tokens/s). CUDA extension not installed. CUDA 12. Install the toolkit and try again. Upload images, audio, and videos by When I load the Airoboros-L2-13B-3. qlinear_cuda:CUDA extension not installed. 1-GPTQ model, I get this warning: auto_gptq. Reload to refresh your session. - AutoGPTQ/AutoGPTQ I tested CUDA 122,121,118, installed 3 versions of bitsandbytes on windows, reinstalled torch in conda, pip, venv, tested different version combinaisons The weird this is, I get good inference perf and no "CUDA extension not installed. Thanks @ Yhyu13, I renamed mixtral to mistral in config. After nnabla-ext-cuda package is installed, you can manually check whether your GPU is usable. py, bloom. Please see its documentation for more instructions: How to fix it? This error indicates AutoGPTQ is not compiling on your system. I tried a lot of methods from other issues, but none worked. 2, but I am not sure if it can be run normally in the environment of . is_available() = true. qlinear_cuda_old:CUDA extension not auto_gptq fails to find a fused CUDA kernel compatible with your environment and falls back to a plain implementation. qlinear_old:CUDA extension not installed. Dec 14, 2023 I still get the "CUDA extension not installed" warning. Follow its installation guide to install a pre-built wheel or try installing 引用auto_gptq时报CUDA extension not installed的提示. 2023-08-23 13:49:27,776 - WARNING - qlinear_old. Collecting auto-gptq Using cached auto_gptq-0. Moreover, using triton the 按文档微调Qwen-7B-Chat后可以正常推理，速度太慢打算量化模型运行run_gpt. utils. " and it takes a long time (minutes?) for the text to generate. 并未在意 If you have run these steps and still get the error, it means that you can't compile the CUDA extension because you don't have CUDA toolkit installed. 2. 6，首先的问题是无法量化。gptq本身是一个github仓库，随后集成在了Transformers 库里，介绍如下：optimum🤗Transformers**已经整合了*，**用于对语言模型进行GPTQ量化。 I am trying to install auto-gptq locally, and I receive this error: Collecting auto-gptq Using cached auto_gptq-0. It means that the AutoGPTQ CUDA extension is not installed, which in 0. 2) and pytorch (appears to be built with 11. On Linux and Windows, AutoGPTQ can be installed through pre-built wheels for specific PyTorch versions: Try reinstalling completely fresh with the oneclick installer, this solved the problem for me. tar. An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm. 1: pip install auto-gptq --no-build-isolation: 2. 2+cu117-cp310-cp310-linux_x86_64. I am installing the tool as a binding in my code directly from python : If you have run these steps and still get the error, it means that you can't compile the CUDA extension because you don't have CUDA toolkit installed. 2 torch 2. ') autogptq_cuda_256 = None autogptq_cuda_64 = None _autogptq_cuda_available = False. I installed cuda in this linux too, but I'm not sure if it was necessary. 0, importing AutoGPTQForCausalLM on Google Colab with an attached GPU (T4) raises this error: WARNING:auto_gptq. ) or you will meet "CUDA not installed" issue. gz (63 kB) Installing build dependencies done Getting requirement "Cuda Extension not installed" Actual systemconfig (python -m torch. by mvetter - opened Dec 14, 2023. json and its working but now I'm getting . Supported Evaluation Tasks. GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers. auto_gptq fails to find a fused CUDA kernel compatible with your environment and falls back to a plain implementation. Running the model using "pip install auto-gptq" still results in "CUDA extension not installed" #3. and the inference is slow. WARNING:auto_gptq. py:16 - CUDA extension not installed. 7. Model Series Qwen2 What are the models used? Qwen2. warning('CUDA extension not installed. model_name_or_path = "TheBloke/Mistral-7B-Instruct-v0. Navigation. I have not tried building auto-gptq==0. CUDA kernels for auto_gptq are not installed, this will result in very slow inference speed. When auto-gptq is install via pip I see messages like "CUDA extension not installed. Currently, auto_gptq supports: LanguageModelingTask, SequenceClassificationTask and TextSummarizationTask; more Tasks will come soon! Running tests. 5. I can run the script with autogptq installed with pip, but get the following error: xllamav2 kernel is not installed, reset disable_exllamav Issue: With transformers and auto_gptq, the logs suggest CUDA extension not installed. 7: Below is an example to extend `auto_gptq` to support `OPT` model, as you will see, it's very easy: from auto_gptq. Error: WARNING:auto_gptq. Here is what I did so far: Created environment with conda; Installed torch / torchvision with cu118 (I do have CUDA 11. I am running into multiple errors when trying to get localGPT to run on my Windows 11 / CUDA machine (3060 / 12 GB). from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline. 8 installed) Installed bitsandbytes for Windows; Cloned this repository and installed requirements I got it all working and then I needed to help someone else run the code and found that I couldn't reproduce the environment. dev20230902+cu121 The Nvidia Cuda Toolkit is not installed. It appears that you were using an auto-gptq package compiled against a different version of CUDA. Luckily I still had another environment where things were fast. xqc kznaq qujqp ujpor bon fxvfh vvgs lzom qmcgq qkei