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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,105 @@
 ---
+base_model: Qwen/Qwen3-8B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- lora
+- qlora
+- peft
+- transformers
+- godot
+- game-development
+- code-generation
+- text-generation
+language:
+- en
 license: apache-2.0
 ---
+
+# SoloLabs GameForge 1
+
+**SoloLabs GameForge** is a QLoRA adapter for [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B), fine-tuned to assist with complete Godot 4 game creation from natural-language prompts. It is intended to generate and explain GDScript, Godot scene trees, project structure, 3D-game mechanics, asset manifests, and Web-preview-oriented build instructions.
+
+This repository contains the **LoRA adapter**, not the full Qwen3-8B base-model weights. The base model is downloaded separately by Transformers from `Qwen/Qwen3-8B`.
+
+## Model details
+
+| Field | Value |
+|---|---|
+| Model name | SoloLabs GameForge 1 |
+| Fine-tuning method | QLoRA / PEFT LoRA |
+| Base model | Qwen/Qwen3-8B |
+| LoRA rank | 16 |
+| LoRA alpha | 32 |
+| LoRA dropout | 0.05 |
+| Target modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
+| Training records | 8,000 total; 6,400 train, 800 validation, 800 test |
+| Intended domain | Godot 4 code and 3D game project generation |
+
+## Intended use
+
+Use the adapter for prototyping Godot 4 projects, generating GDScript and scene-tree plans, drafting 3D-game mechanics, creating asset manifests, and explaining how to validate a generated project. The associated SoloLabs pipeline adds structural project checks, Godot Web export, headless Playwright preview verification, and allowlisted public asset discovery.
+
+The model should be treated as a coding assistant and project generator. Generated code must be reviewed, tested, and security-checked before use. Asset downloads must be independently reviewed for license compatibility before redistribution.
+
+## Important limitations
+
+The adapter is not a standalone 8B model; it must be loaded on top of Qwen3-8B. The model's native output can use a design-object schema, while the production materializer expects a canonical file-list schema. The validated pipeline detects this mismatch, preserves the raw generation, and can use a deterministic procedural fallback for execution.
+
+The Kaggle validation demonstrated a working Godot Web export and headless Playwright verification. Android APK export remained blocked by a Godot 4.4.1 headless Android-preset validation problem in the Kaggle environment. This model card does not claim that every prompt produces a finished commercial game or a guaranteed APK.
+
+## Loading the adapter
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base_id = "Qwen/Qwen3-8B"
+adapter_id = "teja123098/sololabs.1"
+
+tokenizer = AutoTokenizer.from_pretrained(adapter_id, trust_remote_code=True)
+base = AutoModelForCausalLM.from_pretrained(
+    base_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+    trust_remote_code=True,
+)
+model = PeftModel.from_pretrained(base, adapter_id)
+model.eval()
+
+prompt = "Create a Godot 4 third-person 3D arena shooter with a player, two weapons, enemies, pickups, and a Web preview. Return a complete project file manifest with GDScript and scene trees."
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+with torch.no_grad():
+    output = model.generate(**inputs, max_new_tokens=2048, do_sample=False)
+print(tokenizer.decode(output[0], skip_special_tokens=True))
+```
+
+For low-memory inference, load the base model using a compatible 4-bit `BitsAndBytesConfig` and then attach this adapter with `PeftModel.from_pretrained`.
+
+## Training summary
+
+The adapter was trained on Kaggle using QLoRA with 4-bit NF4 quantization, double quantization, FP16 compute, LoRA rank 16, alpha 32, dropout 0.05, and the seven attention/MLP projection target-module groups listed above. The dataset contains 8,000 structured examples covering Godot 4 project generation, GDScript, 3D gameplay, gun-game mechanics, scene trees, asset manifests, Web export, and validation workflows.
+
+## Responsible use
+
+Do not use generated code to introduce malware, evade software protections, infringe third-party assets, or deploy unsafe systems. Review all generated scripts and dependencies. Treat web-discovered assets as untrusted until their source, license, checksum, and compatibility have been verified.
+
+## Related resources
+
+- Base model: [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)
+- Godot Engine: [godotengine.org](https://godotengine.org/)
+- Playwright: [playwright.dev](https://playwright.dev/)
+- SoloLabs GameForge Kaggle notebook: [tej8789/notebookcbedb4fe86](https://www.kaggle.com/code/tej8789/notebookcbedb4fe86)
+- Training adapter source dataset: [tej8789/sololabs-gameforge-qwen3-8b-lora-v8](https://www.kaggle.com/datasets/tej8789/sololabs-gameforge-qwen3-8b-lora-v8)
+
+## Citation
+
+```bibtex
+@misc{sololabs_gameforge_2026,
+  title  = {SoloLabs GameForge 1},
+  author = {SoloLabs},
+  year   = {2026},
+  note   = {QLoRA adapter for Qwen3-8B specialized in Godot 4 game generation}
+}
+```

adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3-8B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "o_proj",
+    "up_proj",
+    "v_proj",
+    "q_proj",
+    "k_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

chat_template.jinja

@@ -0,0 +1,89 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b064181fd20c7d19d5613f061552279d7dcbb8210ffde80386e2a9a6ddf996e7
+size 11422748

tokenizer_config.json

@@ -0,0 +1,29 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "is_local": false,
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4a1b7f4d9839e7122f616461cd3816184a8011fca2950e2c50f952d7481564ee
+size 5201