Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Error when trying to quantize GGUF. #64

Open
Samdoses opened this issue Apr 20, 2024 · 4 comments
Open

Error when trying to quantize GGUF. #64

Samdoses opened this issue Apr 20, 2024 · 4 comments

Comments

@Samdoses
Copy link

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
pandas-stubs 2.0.3.230814 requires numpy>=1.25.0; python_version >= "3.9", but you have numpy 1.24.4 which is incompatible.
tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 4.25.3 which is incompatible.
torchaudio 2.2.1+cu121 requires torch==2.2.1, but you have torch 2.1.2 which is incompatible.
torchtext 0.17.1 requires torch==2.2.1, but you have torch 2.1.2 which is incompatible.
torchvision 0.17.1+cu121 requires torch==2.2.1, but you have torch 2.1.2 which is incompatible.
Successfully installed einops-0.7.0 gguf-0.6.0 numpy-1.24.4 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.18.1 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.1.105 protobuf-4.25.3 torch-2.1.2 triton-2.1.0
WARNING: The following packages were previously imported in this runtime:
[numpy]
You must restart the runtime in order to use newly installed versions.

@Samdoses
Copy link
Author

Samdoses commented Apr 20, 2024

I understand that the wrong version of several dependencies are being installed from the requirements.txt of llama.cpp. Is there any way to manually set the misbehaving dependencie's version myself in the collab code?

Thanks!

@mlabonne
Copy link
Owner

mlabonne commented Apr 20, 2024 via email

@Samdoses
Copy link
Author

I tried installing the dependencies, but they seem to be uninstalled immediately. Is there a way to prevent this and force the code to use the updated versions instead of those specified in the requirements file?

Attempting uninstall: protobuf
Found existing installation: protobuf 3.20.3
Uninstalling protobuf-3.20.3:
Successfully uninstalled protobuf-3.20.3
Attempting uninstall: numpy
Found existing installation: numpy 1.25.2
Uninstalling numpy-1.25.2:
Successfully uninstalled numpy-1.25.2
Attempting uninstall: torch
Found existing installation: torch 2.2.1+cu121
Uninstalling torch-2.2.1+cu121:
Successfully uninstalled torch-2.2.1+cu121

@jazelly
Copy link

jazelly commented May 9, 2024

Hi, have you considered using venv or conda? Looks like you got some existing deps that are unhappy with the requirements.txt that you are trying to install

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants