[Bug] for internlm/internlm-xcomposer2d5-7b-4bit fine tune (ValueError: The model you want to train is loaded in 8-bit precision. if you want to fine-tune an 8-bit model, please make sure that you have installed `bitsandbytes>=0.37.0`)

Hello, I was trying to make fine tuning of `internlm/internlm-xcomposer2d5-7b-4bit` model.

After run `sh finetune_lora.sh` from `~/InternLM-XComposer/finetune` I have get the following issue:

Traceback:
```
trainable params: 151,003,136 || all params: 11,246,729,216 || trainable%: 1.342640452169663
Loading data...
Load 10 samples from ['data/single_turn_single_image_example.json', '0.01']
init mix data at rank 0
load 10 data
5samples is loaded
True
/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/accelerate/accelerator.py:451: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches']). Please pass an `accelerate.DataLoaderConfiguration` instead:
dataloader_config = DataLoaderConfiguration(dispatch_batches=None)
warnings.warn(
Traceback (most recent call last):
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 314, in
train()
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 301, in train
trainer = Trainer(
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/transformers/trainer.py", line 409, in __init__
raise ValueError(
ValueError: The model you want to train is loaded in 8-bit precision. if you want to fine-tune an 8-bit model, please make sure that you have installed `bitsandbytes>=0.37.0`.
trainable params: 151,003,136 || all params: 11,246,729,216 || trainable%: 1.342640452169663
init mix data at rank 1
load 10 data
5samples is loaded
True
/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/accelerate/accelerator.py:451: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches']). Please pass an `accelerate.DataLoaderConfiguration` instead:
dataloader_config = DataLoaderConfiguration(dispatch_batches=None)
warnings.warn(
Traceback (most recent call last):
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 314, in
train()
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 301, in train
trainer = Trainer(
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/transformers/trainer.py", line 409, in __init__
raise ValueError(
ValueError: The model you want to train is loaded in 8-bit precision. if you want to fine-tune an 8-bit model, please make sure that you have installed `bitsandbytes>=0.37.0`.
trainable params: 151,003,136 || all params: 11,246,729,216 || trainable%: 1.342640452169663
init mix data at rank 3
load 10 data
5samples is loaded
True
/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/accelerate/accelerator.py:451: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches']). Please pass an `accelerate.DataLoaderConfiguration` instead:
dataloader_config = DataLoaderConfiguration(dispatch_batches=None)
warnings.warn(
Traceback (most recent call last):
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 314, in
train()
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 301, in train
trainer = Trainer(
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/transformers/trainer.py", line 409, in __init__
raise ValueError(
ValueError: The model you want to train is loaded in 8-bit precision. if you want to fine-tune an 8-bit model, please make sure that you have installed `bitsandbytes>=0.37.0`.
trainable params: 151,003,136 || all params: 11,246,729,216 || trainable%: 1.342640452169663
init mix data at rank 2
load 10 data
5samples is loaded
True
/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/accelerate/accelerator.py:451: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches']). Please pass an `accelerate.DataLoaderConfiguration` instead:
dataloader_config = DataLoaderConfiguration(dispatch_batches=None)
warnings.warn(
Traceback (most recent call last):
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 314, in
train()
File "/home/ubuntu/InternLM-XComposer/finetune/finetune.py", line 301, in train
trainer = Trainer(
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/transformers/trainer.py", line 409, in __init__
raise ValueError(
ValueError: The model you want to train is loaded in 8-bit precision. if you want to fine-tune an 8-bit model, please make sure that you have installed `bitsandbytes>=0.37.0`.
WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 49094 closing signal SIGTERM
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 1 (pid: 49095) of binary: /home/ubuntu/miniconda3/envs/intern_clean/bin/python
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/intern_clean/bin/torchrun", line 8, in
sys.exit(main())
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 346, in wrapper
return f(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/torch/distributed/run.py", line 794, in main
run(args)
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/torch/distributed/run.py", line 785, in run
elastic_launch(
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
return launch_agent(self._config, self._entrypoint, list(args))
File "/home/ubuntu/miniconda3/envs/intern_clean/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
finetune.py FAILED
------------------------------------------------------------
Failures:
[1]:
time : 2024-07-30_09:09:49
host : ip-172-31-18-91.ec2.internal
rank : 2 (local_rank: 2)
exitcode : 1 (pid: 49096)
error_file:
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
time : 2024-07-30_09:09:49
host : ip-172-31-18-91.ec2.internal
rank : 3 (local_rank: 3)
exitcode : 1 (pid: 49097)
error_file:
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
time : 2024-07-30_09:09:49
host : ip-172-31-18-91.ec2.internal
rank : 1 (local_rank: 1)
exitcode : 1 (pid: 49095)
error_file:
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
```

Sending info regarding my env:
```
sys.platform: linux
Python: 3.9.19 (main, May 6 2024, 19:43:03) [GCC 11.2.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0,1,2,3: NVIDIA A10G
CUDA_HOME: /usr/local/cuda-12.1
NVCC: Cuda compilation tools, release 12.1, V12.1.105
GCC: gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.0.1+cu117
PyTorch compiling details: PyTorch built with:
- GCC 9.3
- C++ Version: 201703
- Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 11.7
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
- CuDNN 8.9.7 (built against CUDA 12.2)
- Built with CuDNN 8.5
- Magma 2.6.1
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.5.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.0.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.15.2+cu117
LMDeploy: 0.5.1+5840351
transformers: 4.33.2
gradio: 4.13.0
fastapi: 0.111.1
pydantic: 2.8.2
triton: 2.0.0
NVIDIA Topology:
GPU0 GPU1 GPU2 GPU3 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X PHB PHB PHB 0-47 0 N/A
GPU1 PHB X PHB PHB 0-47 0 N/A
GPU2 PHB PHB X PHB 0-47 0 N/A
GPU3 PHB PHB PHB X 0-47 0 N/A
```