Instructions to use MG31/dfmdetr1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MG31/dfmdetr1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="MG31/dfmdetr1")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("MG31/dfmdetr1") model = AutoModelForObjectDetection.from_pretrained("MG31/dfmdetr1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MG31/dfmdetr1: direct link, hf CLI and curl.
- Browser
- Download file 165 MB
-
https://huggingface.co/MG31/dfmdetr1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MG31/dfmdetr1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MG31/dfmdetr1/resolve/main/pytorch_model.bin
165 MB
- Xet hash:
- e0e976a977f4eb8cdf0ec3b7b0cf81c33fb4d50c65720fe0117dc119d5e47d45
- Size of remote file:
- 165 MB
- SHA256:
- 7d78ce07d50a53a5aae6ac29574fc21b5dc586eae57d2e54d0339ae169615aa0
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