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AlekseyCalvin/LFM3-VL-2B-3D-Coder-SFT

AI model by AlekseyCalvin

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Supervised fine-tune of LiquidAI/LFM3-VL-2B for generating executable Three.js scenes (and GLB-exportable assets) from natural-language instructions. A quasi-reproduction of ccore's Qwen3.5-4B-3D-Coder study. This repo is the plain cross-entropy SFT run (losstype='nll'). An earlier DFT run on this account showed a step-200 generation collapse (repetitive reasoning, no HTML), so this run uses regular SFT at a lower learning rate with a blocking HTML-emission gate every 200 steps. The previous run's artifacts are preserved untouched in AlekseyCalvin/LFM3-VL-2B-3D-Coder. pre-masked labels. ChatML with reasoning preserved. dropout 0, bias none. Language-model targets q/k/v/o/gate/inproj/outproj/w1/w2/w3 (incl. LFM3's gateproj); vision encoder frozen. 65,874,944 trainable params (3.32%). (seed=42) ccore/ThreeJS-3D-GLB-Assets (conversations) samples. maxlength=None, no truncation — examples longer than 24,576 tokens are excluded (an L4 cannot train longer sequences), the rest kept whole. weight decay 0.01, β=(0.9, 0.999), ε=1e-8, bf16, 1 epoch. the 24,576-token filter are what fit; Unsloth gradient checkpointing on. live status.json + metrics.jsonl heartbeat every 10…

AlekseyCalvin/LFM3-VL-2B-3D-Coder-SFT on Hugging Face A short preview, not the full document.

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  1. LFM3-VL-2B 3D Coder — regular SFT
  2. Training configuration
  3. Evaluation
  4. Repository layout
  5. Usage
  6. Results

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AlekseyCalvin/LFM3-VL-2B-3D-Coder-SFT is a task-unspecified model repository published by AlekseyCalvin on Hugging Face. A library was not reported.

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Created
2026-11-10T06:49:18.000Z
Last modified
2026-11-10T06:56:06.000Z

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