Comments (8)
Getting the above problem during execution of the default config.yml. I am beginner pl help me resole this issues
from llm-finetuning-toolkit.
Hi @jeetendraabvv. I'm seeing Click to add a cell.
in your output. Are you running this inside a notebook? tqdm
might not be working as intended inside an interactive session such as jupyter
.
If that's the case I would encourage you to run the CLI directly via command line. And hopefully that solves the problem. If not, let me know!
from llm-finetuning-toolkit.
Thank you @benjaminye . After your suggestion it worked but its generated new error. It is
RuntimeError: Failed to import transformers.integrations.bitsandbytes because of
the following error (look up to see its traceback):
CUDA Setup failed despite GPU being available. Please run the following
command to get more information:
python -m bitsandbytes
Inspect the output of the command and see if you can locate CUDA
libraries. You might need to add them
to your LD_LIBRARY_PATH. If you suspect a bug, please take the
information from python -m bitsandbytes
and open an issue at: https://github.com/TimDettmers/bitsandbytes/issues
I tried the following command to resove the issues but not get success
PS C:\Users\Administrator> pip install bitsandbytes
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com/
Requirement already satisfied: bitsandbytes in c:\programdata\anaconda3\envs\llm_tkit\lib\site-packages (0.42.0)
Requirement already satisfied: scipy in c:\programdata\anaconda3\envs\llm_tkit\lib\site-packages (from bitsandbytes) (1.13.0)
Requirement already satisfied: numpy<2.3,>=1.22.4 in c:\programdata\anaconda3\envs\llm_tkit\lib\site-packages (from scipy->bitsandbytes) (1.26.4)
PS C:\Users\Administrator>
PS C:\Users\Administrator> python -m bitsandbytes
False
===================================BUG REPORT===================================
C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\cuda_setup\main.py:167: UserWarning: Welcome to bitsandbytes. For bug reports, please run
python -m bitsandbytes
warn(msg)
The following directories listed in your path were found to be non-existent: {WindowsPath('C')}
C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\cuda_setup\main.py:167: UserWarning: C:\ProgramData\anaconda3\envs\llm_tkit did not contain ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] as expected! Searching further paths...
warn(msg)
The following directories listed in your path were found to be non-existent: {WindowsPath('http'), WindowsPath('/localhost'), WindowsPath('8888')}
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: {WindowsPath('/usr/local/cuda/lib64')}
DEBUG: Possible options found for libcudart.so: set()
CUDA SETUP: PyTorch settings found: CUDA_VERSION=121, Highest Compute Capability: 8.6.
CUDA SETUP: To manually override the PyTorch CUDA version please see:https://github.com/TimDettmers/bitsandbytes/blob/main/how_to_use_nonpytorch_cuda.md
CUDA SETUP: Loading binary C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\libbitsandbytes_cuda121.so...
argument of type 'WindowsPath' is not iterable
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://raw.githubusercontent.com/TimDettmers/bitsandbytes/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
Traceback (most recent call last):
File "", line 189, in run_module_as_main
File "", line 148, in get_module_details
File "", line 112, in get_module_details
File "C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes_init.py", line 6, in
from . import cuda_setup, utils, research
File "C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\research_init.py", line 1, in
from . import nn
File "C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\research\nn_init.py", line 1, in
from .modules import LinearFP8Mixed, LinearFP8Global
File "C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\research\nn\modules.py", line 8, in
from bitsandbytes.optim import GlobalOptimManager
File "C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\optim_init_.py", line 6, in
from bitsandbytes.cextension import COMPILED_WITH_CUDA
File "C:\ProgramData\anaconda3\envs\llm_tkit\Lib\site-packages\bitsandbytes\cextension.py", line 20, in
raise RuntimeError('''
RuntimeError:
CUDA Setup failed despite GPU being available. Please run the following command to get more information:
from llm-finetuning-toolkit.
Can you send us the output after running transformers-cli env
?
Do you know if your machine is set up to run cuda
(good way to test is by running nvidia-smi
)?
If not, please install by following the instructions here: https://developer.nvidia.com/cuda-12-1-0-download-archive.
In any case, I recommend using linux to run this, on Windows you can use WSL.
from llm-finetuning-toolkit.
PS C:\Users\Administrator\Pictures\lll_tk> transformers-cli env
Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.
transformers
version: 4.40.2- Platform: Windows-10-10.0.20348-SP0
- Python version: 3.11.9
- Huggingface_hub version: 0.23.0
- Safetensors version: 0.4.3
- Accelerate version: 0.27.2
- Accelerate config: not found
- PyTorch version (GPU?): 2.3.0+cu121 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?:
- Using distributed or parallel set-up in script?:
from llm-finetuning-toolkit.
can we use the bitsandbytes >=43.0 with llm_toolkit
from llm-finetuning-toolkit.
Related Issues (20)
- Add comment to indicate tf32 won't be available for older GPUs HOT 1
- `pipx` installation doesn't work HOT 1
- Allow custom train/test datasets
- Add ROADMAP section to the Readme HOT 1
- Change `infer_all` to `infer_test_set` for inference module
- Add unit tests for the code. HOT 1
- Remove unused `accelerate` code
- Allow users to set verbosity of outputs
- Make column variable format in prompt `{{ var }}` instead of `{ var }`
- Quickstart Basic uses a very large model and is slow. HOT 1
- Trying to access gated repo error, Quickstart Basic HOT 2
- quickstart basic - missing qa/llm_tests:? HOT 2
- example config file to run inference only on fine-tuned model HOT 2
- [CLI] Add `llmtune inference [experiment_dir]`
- JSON output test HOT 1
- cuda device-side runtime error when training on custom dataset for JSON outputs HOT 4
- UnicodeEncodeError: 'charmap' codec can't encode character '\u2264' in position in command prompt HOT 2
- After Running command llmtune run ./config.yml not getting output HOT 3
- [LLM Test] Exact Match
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from llm-finetuning-toolkit.