71 lines
1.7 KiB
Markdown
71 lines
1.7 KiB
Markdown
---
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base_model: Qwen/Qwen3-1.7B
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tags:
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- peft
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- lora
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- text-generation
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---
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# Qwen3-1.7B-seed_gen_voronoi
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## Model Description
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Fine-tuned from `Qwen/Qwen3-1.7B` using QLoRA (4-bit) with supervised fine-tuning.
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## Training Details
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- Dataset: `Dannys0n/test-dataset`
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- LoRA rank: 16, alpha: 32
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- Epochs: 3, Learning rate: 0.0002
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## Intended Use
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This model is a test model used for the CS-394/594 class at DigiPen.
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The model is designed to provide seed vectors as structured json for generating voronoi diagrams.
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This can be used just by prompting the model with the example prompt for output,
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or you can run a local server in LMstudio and run this python notebook locally for generating voronoi visualizations as well
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https://github.com/dannys0n/CS394-MyModulesRepo/tree/main/notebooks/07
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## Limitations
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This model is a single-turn model and has not been trained on support long, multi-turn conversations.
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## Example Prompt
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You are placing shard seed centers in a normalized 2D world.
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Coordinates are in [0,1] x [0,1].
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The world aspect ratio is width/height.
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Goal:
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Place K shard centers that balance load from hotspots.
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Hotspots represent player density and include:
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- x, y position
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- weight (importance)
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- radius (influence area)
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Guidelines:
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- Keep shard centers within [0,1] bounds
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- Prefer placing centers near clusters of hotspots
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- Avoid placing centers too close together
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- Try to distribute centers so hotspot load is balanced
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Return ONLY valid JSON.
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OUTPUT FORMAT:
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{
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"seeds": [
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{"x": float, "y": float}
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]
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}
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INPUT_JSON:
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{
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"aspect_ratio": 0.5,
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"k": 4,
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"hotspots": [
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{"x": 0.85, "y": 0.74, "weight": 0.32, "radius": 0.04},
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{"x": 0.98, "y": 0.60, "weight": 0.31, "radius": 0.02},
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{"x": 0.32, "y": 0.41, "weight": 0.18, "radius": 0.06}
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]
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} |