Instructions to use bpdevai/test_detr_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bpdevai/test_detr_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="bpdevai/test_detr_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("bpdevai/test_detr_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("bpdevai/test_detr_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2033/optimizer.pt from bpdevai/test_detr_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 346 MB
-
https://huggingface.co/bpdevai/test_detr_finetuned_cppe5/resolve/main/checkpoint-2033/optimizer.pt
- Command line
-
hf download hf://bpdevai/test_detr_finetuned_cppe5/checkpoint-2033/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/bpdevai/test_detr_finetuned_cppe5/resolve/main/checkpoint-2033/optimizer.pt
346 MB
- Xet hash:
- 5cfe46476bffb3f9f4b3bc33399987cc82a8a637d1b83091e8cfb69455c7b8d1
- Size of remote file:
- 346 MB
- SHA256:
- 34c96518b61b3ccc94b4e381a7083b1354b1034ad6fd4c2321aa4bcdf70688ed
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