I'm running a finetuning unsloth python code in a colab notebook without subscription and I want to save the gguf in my google drive space directly but the function returns an error. I want to do this because the notebook's hard disk capacity is limited. It works without problem for merged16bits or other but not for gguf.
RuntimeError: Unsloth: Quantization failed for .//content/drive/MyDrive/AI/ModelsTensorsWeights/Model_Tokenizer_Unsloth_Phi3mini4kI_merged_q4_k_m_fGGUF/unsloth.BF16.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 --recursive https://github.com/ggerganov/llama.cpp
cd llama.cpp && make clean && make all -j
Once that's done, redo the quantization.
It works without problem for merged16bits or other but not for gguf.
model.save_pretrained_merged("/content/drive/MyDrive/AI/ModelsTensorsWeights/Model_Tokenizer_Unsloth_Llama31_8Bbnb4b_merged_16b_fHF", tokenizer, save_method = "merged_16bit",)
but for GGUF I use !mv command for move gguf file notebook to google drive :
I'm running a finetuning unsloth python code in a colab notebook without subscription and I want to save the gguf in my google drive space directly but the function returns an error. I want to do this because the notebook's hard disk capacity is limited. It works without problem for merged16bits or other but not for gguf.
It works without problem for merged16bits or other but not for gguf.
model.save_pretrained_merged("/content/drive/MyDrive/AI/ModelsTensorsWeights/Model_Tokenizer_Unsloth_Llama31_8Bbnb4b_merged_16b_fHF", tokenizer, save_method = "merged_16bit",)
but for GGUF I use !mv command for move gguf file notebook to google drive :do you think this problem can be solved directly in unsloth ?
Thanks for your great work !