llama.cpp GGUF breaks [FIXED]

[danielhanchen]

As of 3rd December 2024 - fixed.

Please update Unsloth via

pip install --upgrade --no-deps --no-cache-dir unsloth

[criogennn]

RuntimeError                              Traceback (most recent call last)
Cell In[13], [line 12](vscode-notebook-cell:?execution_count=13&line=12)
      [9](vscode-notebook-cell:?execution_count=13&line=9) if False: model.push_to_hub_gguf("hf/model", tokenizer, quantization_method = "f16", token = "")
     [11](vscode-notebook-cell:?execution_count=13&line=11) # Save to q4_k_m GGUF
---> [12](vscode-notebook-cell:?execution_count=13&line=12) if True: model.save_pretrained_gguf("model", tokenizer, quantization_method = "q4_k_m")
     [13](vscode-notebook-cell:?execution_count=13&line=13) if False: model.push_to_hub_gguf("hf/model", tokenizer, quantization_method = "q4_k_m", token = "")
     [15](vscode-notebook-cell:?execution_count=13&line=15) # Save to multiple GGUF options - much faster if you want multiple!

File ~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1683, in unsloth_save_pretrained_gguf(self, save_directory, tokenizer, quantization_method, first_conversion, push_to_hub, token, private, is_main_process, state_dict, save_function, max_shard_size, safe_serialization, variant, save_peft_format, tags, temporary_location, maximum_memory_usage)
   [1681](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1681) python_install = install_python_non_blocking(["gguf", "protobuf"])
   [1682](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1682) git_clone.wait()
-> [1683](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1683) makefile = install_llama_cpp_make_non_blocking()
   [1684](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1684) new_save_directory, old_username = unsloth_save_model(**arguments)
   [1685](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1685) python_install.wait()

File ~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:778, in install_llama_cpp_make_non_blocking()
    [776](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:776) check = os.system("cmake llama.cpp -B llama.cpp/build -DBUILD_SHARED_LIBS=OFF -DGGML_CUDA=OFF -DLLAMA_CURL=ON")
    [777](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:777) if check != 0:
--> [778](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:778)     raise RuntimeError(f"*** Unsloth: Failed compiling llama.cpp using os.system(...) with error {check}. Please report this ASAP!")
    [779](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:779) pass
    [780](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:780) # f"cmake --build llama.cpp/build --config Release -j{psutil.cpu_count()*2} --clean-first --target {' '.join(LLAMA_CPP_TARGETS)}",

RuntimeError: *** Unsloth: Failed compiling llama.cpp using os.system(...) with error 32512. Please report this ASAP!

Error on

if True: model.save_pretrained_gguf("model", tokenizer, quantization_method = "q4_k_m")

model unsloth/Llama-3.2-3B-Instruct
GPU RTX 3050 8GB

pytorch 2.5.1

[criogennn]

install cmake and get this one

RuntimeError                              Traceback (most recent call last)
File ~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1689, in unsloth_save_pretrained_gguf(self, save_directory, tokenizer, quantization_method, first_conversion, push_to_hub, token, private, is_main_process, state_dict, save_function, max_shard_size, safe_serialization, variant, save_peft_format, tags, temporary_location, maximum_memory_usage)
   [1688](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1688) try:
-> [1689](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1689)     new_save_directory, old_username = unsloth_save_model(**arguments)
   [1690](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:1690)     makefile = None

File ~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/torch/utils/_contextlib.py:116, in context_decorator.<locals>.decorate_context(*args, **kwargs)
    [115](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/torch/utils/_contextlib.py:115) with ctx_factory():
--> [116](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/torch/utils/_contextlib.py:116)     return func(*args, **kwargs)

File ~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:714, in unsloth_save_model(model, tokenizer, save_directory, save_method, push_to_hub, token, is_main_process, state_dict, save_function, max_shard_size, safe_serialization, variant, save_peft_format, use_temp_dir, commit_message, private, create_pr, revision, commit_description, tags, temporary_location, maximum_memory_usage)
    [713](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:713) else:
--> [714](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:714)     internal_model.save_pretrained(**save_pretrained_settings)
    [715](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:715) pass

File ~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2938, in PreTrainedModel.save_pretrained(self, save_directory, is_main_process, state_dict, save_function, push_to_hub, max_shard_size, safe_serialization, variant, token, save_peft_format, **kwargs)
   [2937](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2937) for name in disjoint_names:
-> [2938](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2938)     state_dict[name] = state_dict[name].clone()
   [2940](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2940) # When not all duplicates have been cleaned, still remove those keys, but put a clear warning.
   [2941](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2941) # If the link between tensors was done at runtime then `from_pretrained` will not get
   [2942](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2942) # the key back leading to random tensor. A proper warning will be shown
   [2943](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2943) # during reload (if applicable), but since the file is not necessarily compatible with
   [2944](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/transformers/modeling_utils.py:2944) # the config, better show a proper warning.
...
--> [778](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:778)     raise RuntimeError(f"*** Unsloth: Failed compiling llama.cpp using os.system(...) with error {check}. Please report this ASAP!")
    [779](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:779) pass
    [780](https://vscode-remote+wsl-002bubuntu.vscode-resource.vscode-cdn.net/home/neuro/~/miniconda3/envs/unsloth_env/lib/python3.11/site-packages/unsloth/save.py:780) # f"cmake --build llama.cpp/build --config Release -j{psutil.cpu_count()*2} --clean-first --target {' '.join(LLAMA_CPP_TARGETS)}",

RuntimeError: *** Unsloth: Failed compiling llama.cpp using os.system(...) with error 256. Please report this ASAP!

[criogennn]

Before updating unsloth, I encountered the error "CUDA driver error: out of memory". After updating yesterday, the error changed to the one described above. This issue arises when I attempt to save a model in GGUF 4-bit format to run it later in Ollama. Is the 8GB memory of my RTX 3050 insufficient for this task? Training the model completed successfully; the problem occurs specifically during the saving process. I would greatly appreciate any advice or assistance.