TempFit checkpoint

Model weights for template-based industrial CAD scene reconstruction.

The tempfit-scratch directory contains model.safetensors and its companion model.json. The model weights occupy approximately 508.49 MB. The accompanying metadata provides the configuration and file checksums used by TempFit.

Usage

Install TempFit and place the dataset under its data/ and splits/ directories. Download the weights from the repository root:

pip install -U huggingface_hub
hf download Daisy-1227/TempFit --include "tempfit-scratch/*" --local-dir checkpoints

Run autoregressive inference:

python inference.py --config configs/inference.yaml --checkpoint checkpoints/tempfit-scratch/model.safetensors --output_dir outputs/tempfit-scratch

Initialize a new training run from these weights:

accelerate launch --multi_gpu --num_processes 8 --mixed_precision bf16 train.py --config configs/train.yaml --pretrained checkpoints/tempfit-scratch/model.safetensors --output_dir outputs/tempfit-scratch-finetune

For a single GPU:

python train.py --config configs/train.yaml --pretrained checkpoints/tempfit-scratch/model.safetensors --output_dir outputs/tempfit-scratch-finetune

Gradient accumulation adjusts to preserve the default global batch size of 128.

Keep model.json alongside its weight file. The package supports inference and pretrained initialization; optimizer and scheduler states are excluded.

License

The weights are released under the MIT License. Dataset access and use are governed separately by the dataset license.

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