llm-course: Pls help, stuck with AutoGGUF

I tried to make ggufs of different models (one that was already available and one which I made using the lazymergekit).

I always get the same error how ever. It’s this one (I edited the model name out but it happens with both I tested. They are Mistral 7b based ones):

GML_CUDA_FORCE_MMQ:   no
ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes
ggml_init_cublas: found 1 CUDA devices:
  Device 0: Tesla T4, compute capability 7.5, VMM: yes
main: build = 2151 (704359e2)
main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: quantizing 'ModelName/modelname.fp16.bin' to 'ModelName/modelname.Q4_K_S.gguf' as Q4_K_S
llama_model_quantize: failed to quantize: failed to open ModelName/modelname.fp16.bin: No such file or directory
main: failed to quantize model from 'ModelName/modelname.fp16.bin'

Also, before that error, I get another error:

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.
lida 0.0.10 requires fastapi, which is not installed.
lida 0.0.10 requires kaleido, which is not installed.
lida 0.0.10 requires python-multipart, which is not installed.
lida 0.0.10 requires uvicorn, which is not installed.
tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 4.25.2 which is incompatible.
torchaudio 2.1.0+cu121 requires torch==2.1.0, but you have torch 2.1.2 which is incompatible.
torchdata 0.7.0 requires torch==2.1.0, but you have torch 2.1.2 which is incompatible.
torchtext 0.16.0 requires torch==2.1.0, but you have torch 2.1.2 which is incompatible.
torchvision 0.16.0+cu121 requires torch==2.1.0, but you have torch 2.1.2 which is incompatible.
Successfully installed 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-cu12-12.3.101 nvidia-nvtx-cu12-12.1.105 protobuf-4.25.2 torch-2.1.2

WARNING: The following packages were previously imported in this runtime:
  [numpy]
You must restart the runtime in order to use newly installed versions.

Is there any solution? I would like to try the model I merged locally, I was even able to evaluate it in the leaderboard but I can’t turn it into GGUF. Also is there a dedicated GitHub page for that notebook?