fix: update GGUF save paths to use ~/.unsloth/llama.cpp with Windows support (#4138)

* fix: update GGUF save paths to use ~/.unsloth/llama.cpp with Windows support

* fix: quote LLAMA_CPP_DEFAULT_DIR in fallback shell commands to handle paths with spaces

* refactor: deduplicate platform-specific build instructions in quantization error message

* chore: remove accidentally committed PR description file

* Fix import safety and f-string bugs in save.py

- H4: Add defensive try/except for LLAMA_CPP_DEFAULT_DIR and IS_WINDOWS imports
  with fallback defaults, so save.py works even if zoo PR #526 is not merged yet
- H5: Fix Kaggle error path using plain "Error: {e}" instead of f"Error: {e}",
  so the actual exception is shown to users

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: Datta Nimmaturi <venkatadattasainimmaturi@gmail.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

unsloth/save.py

@@ -23,6 +23,16 @@ from unsloth_zoo.llama_cpp import (
     check_llama_cpp,
     _download_convert_hf_to_gguf,
 )
+
+# H4: Defensive imports -- these were added in unsloth-zoo PR #526
+# and may not exist on older versions
+try:
+    from unsloth_zoo.llama_cpp import LLAMA_CPP_DEFAULT_DIR, IS_WINDOWS
+except ImportError:
+    import sys
+
+    IS_WINDOWS = sys.platform == "win32"
+    LLAMA_CPP_DEFAULT_DIR = "llama.cpp"
 from bitsandbytes.nn import Linear4bit as Bnb_Linear4bit
 from peft.tuners.lora import Linear4bit as Peft_Linear4bit
 from peft.tuners.lora import Linear as Peft_Linear
@@ -1316,18 +1326,26 @@ def save_to_gguf(
                             "`model.{save_pretrained/push_to_hub}_gguf will use too much disk space.\n"
                             "You can try saving it to the `/tmp` directory for larger disk space.\n"
                             "I suggest you to save the 16bit model first, then use manual llama.cpp conversion.\n"
-                            "Error: {e}"
+                            f"Error: {e}"
                         )
                     else:
+                        if IS_WINDOWS:
+                            build_instructions = (
+                                f'cd "{LLAMA_CPP_DEFAULT_DIR}"\n'
+                                f"cmake -S . -B build -DBUILD_SHARED_LIBS=OFF\n"
+                                f"cmake --build build --config Release"
+                            )
+                        else:
+                            build_instructions = f'cd "{LLAMA_CPP_DEFAULT_DIR}" && make clean && make all -j'
+
                         raise RuntimeError(
                             f"Unsloth: Quantization failed for {output_location}\n"
                             "You might have to compile llama.cpp yourself, then run this again.\n"
                             "You do not need to close this Python program. Run the following commands in a new terminal:\n"
-                            "You must run this in the same folder as you're saving your model.\n"
-                            "git clone --recursive https://github.com/ggerganov/llama.cpp\n"
-                            "cd llama.cpp && make clean && make all -j\n"
+                            f'git clone --recursive https://github.com/ggerganov/llama.cpp "{LLAMA_CPP_DEFAULT_DIR}"\n'
+                            f"{build_instructions}\n"
                             "Once that's done, redo the quantization.\n"
-                            "Error: {e}"
+                            f"Error: {e}"
                         )
         print("Unsloth: Model files cleanup...")
         if quants_created:
@@ -2084,16 +2102,22 @@ def unsloth_save_pretrained_gguf(
             "Unsloth: ##### We removed it in GGUF's chat template for you."
         )
 
+    _exe = ".exe" if IS_WINDOWS else ""
+    if IS_WINDOWS:
+        _bin_dir = os.path.join(LLAMA_CPP_DEFAULT_DIR, "build", "bin", "Release")
+    else:
+        _bin_dir = LLAMA_CPP_DEFAULT_DIR
+
     if is_vlm_update:
         print("\n")
         print(
-            f"Unsloth: example usage for Multimodal LLMs: llama.cpp/llama-mtmd-cli -m {all_file_locations[0]} --mmproj {all_file_locations[-1]}"
+            f"Unsloth: example usage for Multimodal LLMs: {os.path.join(_bin_dir, 'llama-mtmd-cli' + _exe)} -m {all_file_locations[0]} --mmproj {all_file_locations[-1]}"
         )
         print("Unsloth: load image inside llama.cpp runner: /image test_image.jpg")
         print("Unsloth: Prompt model to describe the image")
     else:
         print(
-            f'Unsloth: example usage for text only LLMs: llama.cpp/llama-cli --model {all_file_locations[0]} -p "why is the sky blue?"'
+            f'Unsloth: example usage for text only LLMs: {os.path.join(_bin_dir, "llama-cli" + _exe)} --model {all_file_locations[0]} -p "why is the sky blue?"'
         )
 
     if ollama_success:
@@ -2307,8 +2331,8 @@ tags:
 This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
 
 **Example usage**:
-- For text only LLMs:    `./llama.cpp/llama-cli -hf {repo_id} --jinja`
-- For multimodal models: `./llama.cpp/llama-mtmd-cli -hf {repo_id} --jinja`
+- For text only LLMs:    `llama-cli -hf {repo_id} --jinja`
+- For multimodal models: `llama-mtmd-cli -hf {repo_id} --jinja`
 
 ## Available Model files:
 """