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-1605/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-1605/optimizer.pt
- Command line
-
hf download hf://bpdevai/test_detr_finetuned_cppe5/checkpoint-1605/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/bpdevai/test_detr_finetuned_cppe5/resolve/main/checkpoint-1605/optimizer.pt
346 MB
- Xet hash:
- 9384d8a73b8724e48578a2ff397caaee660c03032999c524075b2230fb862651
- Size of remote file:
- 346 MB
- SHA256:
- 8645f6a3f58d9ba8c9a68892a76d29d774dcac09b1907f08f7fa5aaa04596dd7
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