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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.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

@@ -0,0 +1,47 @@
+---
+language:
+- en
+license: apache-2.0
+tags:
+- qwen
+- html
+- threejs
+- code-generation
+- fine-tuned
+pipeline_tag: text-generation
+---
+
+# qwen3-4b-html-spatial-8bit
+
+This is a fine-tuned version of Qwen3-4B for generating 3D HTML visualizations using Three.js (8-bit).
+
+## Model Details
+
+- **Base Model**: unsloth/Qwen3-4B-Base
+- **Model Type**: 8-bit Quantized
+- **Training Examples**: 5021
+- **Max Sequence Length**: 8192
+- **LoRA Rank**: 64
+- **Final Loss**: 0.2878
+
+## Intended Use
+
+Generate complete HTML (CSS + JS) for 3D scenes using Three.js r128 from natural language prompts.
+
+## System Prompt
+
+```text
+You are an expert in generating 3D HTML visualizations using Three.js. Given a user prompt describing a 3D scene or spatial concept, generate clean, functional HTML code with embedded JavaScript and CSS. Always use Three.js r128 from cdnjs and include all necessary script imports for GLTFLoader, OrbitControls, and other addons when needed.
+```
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("Ashwin999/qwen3-4b-html-spatial-8bit")
+tokenizer = AutoTokenizer.from_pretrained("Ashwin999/qwen3-4b-html-spatial-8bit")
+
+prompt = "Create a rotating 3D cube"
+# Generate HTML...
+```

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen3ForCausalLM",
+    "parent_library": "transformers.models.qwen3.modeling_qwen3",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/Qwen3-4B-Base",
+  "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": 128,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "gate_proj",
+    "q_proj",
+    "o_proj",
+    "up_proj",
+    "k_proj",
+    "v_proj",
+    "down_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 528550256

added_tokens.json

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chat_template.jinja

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+{% if messages[0]['role'] == 'system' %}{{ messages[0]['content'] + eos_token }}{% set loop_messages = messages[1:] %}{% else %}{{ 'You are an expert in generating 3D HTML visualizations using Three.js. Given a user prompt describing a 3D scene or spatial concept, generate clean, functional HTML code with embedded JavaScript and CSS. Always use Three.js r128 from cdnjs and include all necessary script imports for GLTFLoader, OrbitControls, and other addons when needed.' + eos_token }}{% set loop_messages = messages %}{% endif %}{% for message in loop_messages %}{% if message['role'] == 'user' %}{{ message['content'] + eos_token }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '' }}{% endif %}

special_tokens_map.json

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+}

tokenizer.json

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+oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
+size 11422654

tokenizer_config.json

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+}