RuntimeError explanation

what is this error:

From the screenshot you shared, the main error is here: ``` RuntimeError: ... raise RuntimeError( "Unsloath: No working quantizer found in {llama_cpp_folder}\n" ``` This happens at the step where `unsloth` is trying to convert your model to GGUF format: ```python model.save_pretrained_gguf(MERGED_DIR, quantization_method="q4_k_m") ``` The error occurs because the `llama.cpp` folder does not contain a working quantizer. Essentially: 1. `unsloth` is attempting to use `llama.cpp` tools to convert the model to GGUF format. 2. It checks your system for `llama.cpp` binaries using `check_llama_cpp()`. 3. It either doesn't find the binaries or they are incomplete, so it raises a `RuntimeError`. Additional context from the log: - The message: `Unsloath: llama.cpp folder exists but binaries not found – will rebuild` shows it tried to rebuild `llama.cpp`. - Then it fails at the quantizer step because the rebuild didn't produce a working binary. --- **Why this happens:** - `unsloth` requires `llama.cpp` to be compiled with a working `quantize` tool. - Either compilation failed, or your environment (Python 3.13, Linux) caused a binary incompatibility. - Sometimes `llama.cpp` install via `unsloth` is skipped if certain dependencies are missing. --- **How to fix:** 1. Make sure your system has `cmake` and a C++ compiler installed (`g++`, `clang`). ```bash sudo apt update sudo apt install cmake build-essential ``` 2. Delete the existing `llama.cpp` folder under `unsloth` so it forces a rebuild: ```bash rm -rf ~/ai/renovai/unsloth/lib/python3.13/site-packages/unsloth_zo/llama_cpp ``` 3. Re-run your Python code to let `unsloth` rebuild `llama.cpp` binaries. 4. If it still fails, you can manually build `llama.cpp`: ```bash git clone https://github.com/ggerganov/llama.cpp cd llama.cpp make ``` 5. After building, point `unsloth` to your manually built `llama.cpp` folder when calling `save_pretrained_gguf`. --- The **secondary warning**: ``` UserWarning: Model is not a PeftModel (no Lora adapters detected). Skipping Merge. ``` - This is not fatal. It just says there’s no LoRA adapter in your model, so `save_pretrained_merged` will essentially save the original weights. --- ✅ **TL;DR**: Your error is because `unsloth` cannot find a working quantizer in `llama.cpp`. You need to make sure `llama.cpp` is properly built with `cmake` and a C++ compiler. I can give you the exact shell commands to rebuild it for your Python 3.13 environment so `save_pretrained_gguf` works. Do you want me to do that?