Converting Models to GGUF: The DIY Method

Sometimes, you find a amazing new model on Hugging Face that is only available in SafeTensors or PyTorch format. To run this in Ollama, you have to perform a Conversion.

Note: This is an advanced lesson that requires Python and the llama.cpp source code.

1. The Tools You Need

To convert a model, you need the convert_hf_to_gguf.py script from the official llama.cpp repository.

1. Clone the Repo: git clone https://github.com/ggerganov/llama.cpp
2. Install Requirements: pip install -r llama.cpp/requirements.txt

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2. The Conversion Process

Step 1: Download the Raw Model

Use the Hugging Face CLI or simply download the entire repository folder from Hugging Face. Ensure you have the config.json, tokenizer.model, and the large .safetensors files.

Step 2: The Command

Run the Python script pointing to your model folder.

python llama.cpp/convert_hf_to_gguf.py ./my-raw-model-folder --outtype f16 --outfile my-model.gguf

• --outtype f16: This tells the script to save the model in "Full Precision" (16-bit). We will "Quantize" it (make it smaller) in the next lesson.
• --outfile: The name of the file you want to use in Ollama.

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3. Why Not Just Download a GGUF?

You should always try to find a pre-converted GGUF first (look for creators like "Bartowski" or "MaziyarPanahi" on Hugging Face). However, you would do your own conversion if:

• You just fine-tuned your own model (Module 11).
• The model was released minutes ago and no one has converted it yet.
• You want to use a specific, rare quantization method.

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4. Troubleshooting Conversion

• Missing Tokenizer: If the script fails, it's usually because the model folder is missing the tokenizer.json or sentencepiece file.
• Unsupported Architecture: If you see a "Key Error," it means llama.cpp doesn't know how to handle that specific math structure yet. You'll have to wait for an update.

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Summary Checklist

1. Repo: Do you have the llama.cpp scripts?
2. Environment: Is your Python virtual environment ready?
3. Space: Do you have 2x the model size in free disk space? (You need space for the raw model AND the new GGUF).

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Key Takeaways

• Conversion is required to turn SafeTensors/PyTorch into GGUF.
• The process uses Python scripts from the llama.cpp project.
• Start with F16 (Full Precision) during conversion and compress later.
• Pre-converted models from the community save you hours of time and gigabytes of bandwidth.