Add README

README.md

@@ -1,16 +1,31 @@
 ---
-library_name: peft
-base_model: unsloth/gemma-4-E4B-it
 tags:
+- gguf
+- llama.cpp
 - unsloth
-- trl
-- coding-agent
+- vision-language-model
 ---
-# gemma4-coding-agent
 
-This model is a fine-tuned version of `unsloth/gemma-4-E4B-it` for Pythonic function calling and coding tasks.
-It was trained using [Unsloth](https://github.com/unslothai/unsloth).
+# gemma4-coding-agent : GGUF
 
-## Formats
-- **LoRA Adapters:** Available in the root directory.
-- **GGUF:** Available for standard local inference (e.g., LM Studio, Ollama).
+This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
+
+**Example usage**:
+- For text only LLMs:    `llama-cli -hf S4MPL3BI4S/gemma4-coding-agent --jinja`
+- For multimodal models: `llama-mtmd-cli -hf S4MPL3BI4S/gemma4-coding-agent --jinja`
+
+## Available Model files:
+- `gemma-4-E4B-it.Q4_K_M.gguf`
+- `gemma-4-E4B-it.BF16-mmproj.gguf`
+
+## ⚠️ Ollama Note for Vision Models
+**Important:** Ollama currently does not support separate mmproj files for vision models.
+
+To create an Ollama model from this vision model:
+1. Place the `Modelfile` in the same directory as the finetuned bf16 merged model
+3. Run: `ollama create model_name -f ./Modelfile`
+   (Replace `model_name` with your desired name)
+
+This will create a unified bf16 model that Ollama can use.
+This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)