# Ollama: Importing a LoRA/QLoRA Adapter (Gemma 4 applicable)

Source: https://docs.ollama.com/import (fetched 2026-04-18)

## Modelfile syntax

**Safetensors adapter (merged or unmerged):**
```dockerfile
FROM <base model name>
ADAPTER /path/to/safetensors/adapter/directory
```

**GGUF adapter:**
```dockerfile
FROM <base model name>
ADAPTER /path/to/file.gguf
```

## Creation
```shell
ollama create my-model
```

## Critical notes

- **The `FROM` base model MUST match the base the adapter was trained on** or you'll get erratic results. For Gemma 4: `FROM gemma4:e4b-it-q8_0` (or whichever base was used).
- **Non-QLoRA adapters preferred.** Quantized adapter recipes (QLoRA) sometimes diverge in method across frameworks; using a straight LoRA adapter is more portable.
- Gemma 4 is NOT explicitly listed in the Ollama docs' "supported architectures" section (which lists Llama 2/3, Mistral, Gemma 1/2) — but llama.cpp gained Gemma 4 support day one, and the Ollama gemma4 models work. Expect smooth sailing for text; vision adapters are a grey area.

## Converting a PEFT / Unsloth adapter to GGUF

Use llama.cpp's `convert_lora_to_gguf.py`:
```bash
python llama.cpp/convert_lora_to_gguf.py \
    --outfile gemma4-mortdecai-adapter.gguf \
    path/to/peft/adapter_dir
```
Or use HuggingFace's "GGUF-my-LoRA" Space: https://huggingface.co/spaces/ggml-org/gguf-my-lora (web UI).

## Unsloth fast path

Unsloth's notebooks finish with a cell that does exactly:
```python
model.save_pretrained_gguf("model", tokenizer, quantization_method = "q4_k_m")
```
which produces a GGUF suitable for direct `ollama create`.

## Workflow for Seth's homelab

1. Fine-tune with Unsloth on a rented H100/H200 (or local 3090 for E4B).
2. `model.save_pretrained_merged("merged_out", tokenizer, save_method = "merged_16bit")` — save the merged model in 16-bit safetensors.
3. Use llama.cpp's `convert_hf_to_gguf.py` to make a GGUF, then quantize to Q4_K_M.
4. Write a Modelfile pointing at the GGUF, `ollama create mortdecai-gemma4:v1 -f Modelfile`, push to local Ollama (pve197 CT 105 or steel141).