Unsloth: Merging 4bit and LoRA weights to 16bit...
Unsloth: Will use up to 5.34 out of 12.67 RAM for saving.
100%|██████████| 28/28 [01:37<00:00,  3.49s/it]
Unsloth: Saving tokenizer... Done.
Unsloth: Saving model... This might take 5 minutes for Llama-7b...
Unsloth: Saving BramNH/gemma-7b-bnb-4bit-homeassistant-nl/pytorch_model-00001-of-00004.bin...
Unsloth: Saving BramNH/gemma-7b-bnb-4bit-homeassistant-nl/pytorch_model-00002-of-00004.bin...
Unsloth: Saving BramNH/gemma-7b-bnb-4bit-homeassistant-nl/pytorch_model-00003-of-00004.bin...
Unsloth: Saving BramNH/gemma-7b-bnb-4bit-homeassistant-nl/pytorch_model-00004-of-00004.bin...
Done.
==((====))==  Unsloth: Conversion from QLoRA to GGUF information
   \\   /|    [0] Installing llama.cpp will take 3 minutes.
O^O/ \_/ \    [1] Converting HF to GUUF 16bits will take 3 minutes.
\        /    [2] Converting GGUF 16bits to q4_k_m will take 20 minutes.
 "-____-"     In total, you will have to wait around 26 minutes.

Unsloth: [0] Installing llama.cpp. This will take 3 minutes...
Unsloth: [1] Converting model at BramNH/gemma-7b-bnb-4bit-homeassistant-nl into f16 GGUF format.
The output location will be ./BramNH/gemma-7b-bnb-4bit-homeassistant-nl-unsloth.F16.gguf
This will take 3 minutes...
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-27-20e4264a3018> in <cell line: 11>()
      9 # Save to q4_k_m GGUF
     10 if False: model.save_pretrained_gguf("model", tokenizer, quantization_method = "q4_k_m")
---> 11 if True: model.push_to_hub_gguf("BramNH/gemma-7b-bnb-4bit-homeassistant-nl", tokenizer, quantization_method = "q4_k_m", token = "")

1 frames
/usr/local/lib/python3.10/dist-packages/unsloth/save.py in save_to_gguf(model_type, model_directory, quantization_method, first_conversion, _run_installer)
    794     # Check if quantization succeeded!
    795     if not os.path.isfile(final_location):
--> 796         raise RuntimeError(
    797             f"Unsloth: Quantization failed for {final_location}\n"\
    798             "You might have to compile llama.cpp yourself, then run this again.\n"\

RuntimeError: Unsloth: Quantization failed for ./BramNH/gemma-7b-bnb-4bit-homeassistant-nl-unsloth.F16.gguf
You might have to compile llama.cpp yourself, then run this again.
You do not need to close this Python program. Run the following commands in a new terminal:
You must run this in the same folder as you're saving your model.
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp && make clean && LLAMA_CUBLAS=1 make all -j
Once that's done, redo the quantization.