Update README.md

README.md

@@ -1,22 +1,101 @@
 ---
-base_model: unsloth/qwen2.5-coder-7b-instruct-bnb-4bit
-tags:
-- text-generation-inference
-- transformers
-- unsloth
-- qwen2
-- trl
 license: apache-2.0
+base_model: unsloth/Qwen2.5-Coder-7B-Instruct
+tags:
+  - godot
+  - godot4
+  - gdscript
+  - game-development
+  - lora
+  - qlora
+  - unsloth
+  - code
+  - saltshakerstudio
+datasets:
+  - glaiveai/godot_4_docs
 language:
-- en
+  - en
+library_name: peft
+pipeline_tag: text-generation
 ---
 
-# Uploaded  model
+# Qwen2.5-Coder-7B-Instruct — Godot 4 / GDScript LoRA
+
+A LoRA adapter for [unsloth/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/unsloth/Qwen2.5-Coder-7B-Instruct), fine-tuned on Godot 4 documentation Q&A to improve knowledge of modern Godot 4 GDScript syntax and APIs.
+
+**Motivation:** Most open GDScript fine-tunes (e.g. godot-dodo, 2023) were trained on Godot 3 code and produce outdated syntax. Even current code models frequently mix Godot 3 and Godot 4 patterns. This adapter is a first attempt at nudging a modern 7B coder model toward Godot 4 conventions, trained locally on a single consumer GPU.
+
+## Training details
+
+| | |
+|---|---|
+| Base model | unsloth/Qwen2.5-Coder-7B-Instruct |
+| Method | QLoRA (4-bit), via Unsloth Fine-tuning Studio |
+| Dataset | [glaiveai/godot_4_docs](https://huggingface.co/datasets/glaiveai/godot_4_docs) (~3,490 Q&A pairs generated from Godot 4 documentation) |
+| Epochs | 2 |
+| Learning rate | 2e-4, linear schedule |
+| LoRA rank / alpha / dropout | 16 / 16 / 0 |
+| Target modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
+| Batch size | 2 (gradient accumulation 4, effective 8) |
+| Optimizer | AdamW 8-bit, weight decay 0.001 |
+| Max sequence length | 4096 |
+| Hardware | Single RTX 4080 (16 GB), Windows 11 |
+| Training time | ~45 minutes |
+
+Eval loss fell from ~0.83 to ~0.775 and plateaued. Runs at 1, 2, and 3 epochs showed 2 epochs to be the sweet spot for this dataset: 1 epoch left eval loss still declining, 3 epochs overfit (eval loss climbed after epoch 2 and chat-test quality regressed).
+
+## What it improves
+
+Compared to the base model in side-by-side chat tests, the adapter more consistently produces some Godot 4 conventions, for example the `@export` annotation:
+
+```gdscript
+@export var speed: int = 300   # Godot 4 ✅
+# instead of:
+export var speed = 300         # Godot 3 ❌
+```
+
+Responses also tend to be more concise and code-focused, reflecting the Q&A style of the training data.
+
+## Known limitations — read before using
+
+**This adapter does not fully solve the Godot 3 → 4 problem.** In testing, both the base model and this fine-tune still frequently produce Godot 3 patterns, especially:
+
+- **Signal connections** — often writes the old form `button.connect("pressed", self, "_on_pressed")` instead of the Godot 4 form `button.pressed.connect(_on_pressed)`
+- **Character movement** — may use `Sprite2D` or `KinematicBody2D` instead of `CharacterBody2D`, and `move_and_slide(velocity)` instead of `move_and_slide()`
+
+The training dataset is derived from Godot 4 documentation and appears to be thin on these common game-programming patterns, so the model had little opportunity to learn them. Treat generated code as a draft and verify against the [current Godot documentation](https://docs.godotengine.org/en/stable/).
+
+Other caveats:
+
+- Trained and tested in English only
+- Not evaluated on Godot C#, shaders (GDShader), or Godot 3 back-compatibility questions
+- No safety or alignment tuning beyond what the base model provides
+
+## Usage
+
+Load the adapter on top of the base model with PEFT:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base = AutoModelForCausalLM.from_pretrained(
+    "unsloth/Qwen2.5-Coder-7B-Instruct",
+    load_in_4bit=True,
+    device_map="auto",
+)
+tokenizer = AutoTokenizer.from_pretrained("unsloth/Qwen2.5-Coder-7B-Instruct")
+model = PeftModel.from_pretrained(base, "YOUR_USERNAME/YOUR_REPO_NAME")
+```
+
+Or merge and export to GGUF for local runners (llama.cpp, Ollama, LM Studio) — Unsloth Fine-tuning Studio provides an Export to GGUF option.
+
+## Intended use
 
-- **Developed by:** SaltShakerStudio
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/qwen2.5-coder-7b-instruct-bnb-4bit
+Hobbyist / experimental. A starting point for anyone interested in local Godot 4 coding assistants — including eventual use alongside a Godot MCP server, where better Godot 4 knowledge should translate into more correct tool calls. Contributions of better Godot 4 training data (especially signals, movement, and node-setup examples) would likely help more than additional training epochs on the current dataset.
 
-This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
+## Acknowledgements
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+- Base model: Qwen team / Unsloth quantization
+- Dataset: Glaive AI's godot_4_docs
+- Training: Unsloth Fine-tuning Studio