| --- |
| license: mit |
| tags: |
| - cad |
| - template-fitting |
| - pytorch |
| --- |
| |
| # TempFit checkpoint |
|
|
| Model weights for template-based industrial CAD scene reconstruction. |
|
|
| [Code and installation](https://github.com/Daisy-1227/TempFit) · [Dataset](https://huggingface.co/datasets/Daisy-1227/TempFit) |
|
|
| 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: |
|
|
| ```bash |
| pip install -U huggingface_hub |
| hf download Daisy-1227/TempFit --include "tempfit-scratch/*" --local-dir checkpoints |
| ``` |
|
|
| Run autoregressive inference: |
|
|
| ```bash |
| 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: |
|
|
| ```bash |
| 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: |
|
|
| ```bash |
| 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. |
|
|
