解决AttributeError: module ‘bitsandbytes.nn‘ has no attribute ‘Linear8bitLt‘

我之所以发生这个问题，是因为做了下面的操作：

在做量化时，peft包下面tuning目录的lora.py文件中调用了bitsandbytes的nn.Linear8bitLt 对象，但是bitsandbytes-113没有在这个属性

错误安装：

pip install bitsandbytes-113

上面的版本已经不支持了，需要重新装bitsandbytes

正确安装：

pip install bitsandbytes

为什么 进行了：

pip install bitsandbytes-113

是因为我上面遇到了这样错误：

===================================BUG REPORT===================================
/data/conda_env/ft/lib/python3.8/site-packages/bitsandbytes/cuda_setup/main.py:166: UserWarning: Welcome to bitsandbytes. For bug reports, please run

python -m bitsandbytes

  warn(msg)
================================================================================
/data/conda_env/ft/lib/python3.8/site-packages/bitsandbytes/cuda_setup/main.py:166: UserWarning: /data/conda_env/ft did not contain ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] as expected! Searching further paths...
  warn(msg)
CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching in backup paths...
The following directories listed in your path were found to be non-existent: {PosixPath('/usr/local/cuda/lib64')}
DEBUG: Possible options found for libcudart.so: set()
CUDA SETUP: CUDA version lower than 11 are currently not supported for LLM.int8(). You will be only to use 8-bit optimizers and quantization routines!!
CUDA SETUP: PyTorch settings found: CUDA_VERSION=102, Highest Compute Capability: 7.0.
CUDA SETUP: To manually override the PyTorch CUDA version please see:https://github.com/TimDettmers/bitsandbytes/blob/main/how_to_use_nonpytorch_cuda.md

/data/conda_env/ft/lib/python3.8/site-packages/bitsandbytes/cuda_setup/main.py:166: UserWarning: WARNING: Compute capability < 7.5 detected! Only slow 8-bit matmul is supported for your GPU!                     

If you run into issues with 8-bit matmul, you can try 4-bit quantization: https://huggingface.co/blog/4bit-transformers-bitsandbytes
  warn(msg)
CUDA SETUP: Required library version not found: libbitsandbytes_cuda102_nocublaslt.so. Maybe you need to compile it from source?
CUDA SETUP: Defaulting to libbitsandbytes_cpu.so...

================================================ERROR=====================================
CUDA SETUP: CUDA detection failed! Possible reasons:
1. You need to manually override the PyTorch CUDA version. Please see: "https://github.com/TimDettmers/bitsandbytes/blob/main/how_to_use_nonpytorch_cuda.md
2. CUDA driver not installed
3. CUDA not installed
4. You have multiple conflicting CUDA libraries
5. Required library not pre-compiled for this bitsandbytes release!
CUDA SETUP: If you compiled from source, try again with `make CUDA_VERSION=DETECTED_CUDA_VERSION` for example, `make CUDA_VERSION=113`.
CUDA SETUP: The CUDA version for the compile might depend on your conda install. Inspect CUDA version via `conda list | grep cuda`.

CUDA SETUP: Problem: The main issue seems to be that the main CUDA runtime library was not detected.
CUDA SETUP: Solution 1: To solve the issue the libcudart.so location needs to be added to the LD_LIBRARY_PATH variable
CUDA SETUP: Solution 1a): Find the cuda runtime library via: find / -name libcudart.so 2>/dev/null
CUDA SETUP: Solution 1b): Once the library is found add it to the LD_LIBRARY_PATH: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:FOUND_PATH_FROM_1a
CUDA SETUP: Solution 1c): For a permanent solution add the export from 1b into your .bashrc file, located at ~/.bashrc
CUDA SETUP: Solution 2: If no library was found in step 1a) you need to install CUDA.
CUDA SETUP: Solution 2a): Download CUDA install script: wget https://github.com/TimDettmers/bitsandbytes/blob/main/cuda_install.sh
CUDA SETUP: Solution 2b): Install desired CUDA version to desired location. The syntax is bash cuda_install.sh CUDA_VERSION PATH_TO_INSTALL_INTO.
CUDA SETUP: Solution 2b): For example, "bash cuda_install.sh 113 ~/local/" will download CUDA 11.3 and install into the folder ~/local
CUDA SETUP: Setup Failed!
Traceback (most recent call last):

最后我排查了各种原因，比如找不到libcud...so等文件，反复find 文件，然后把路径都补到环境变量里， 

最终的原因还是Nvidia driver 版本太低；

上面的错误信息也提及了：

---

UDA SETUP: CUDA version lower than 11 are currently not supported for LLM.int8(). You will be only to use 8-bit optimizers and quantization routines!!