Instructions to use techtank/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use techtank/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="techtank/detr-resnet-50_finetuned_cppe5")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("techtank/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("techtank/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from techtank/detr-resnet-50_finetuned_cppe5: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/techtank/detr-resnet-50_finetuned_cppe5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://techtank/detr-resnet-50_finetuned_cppe5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/techtank/detr-resnet-50_finetuned_cppe5/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 120a8f0e7da2141a5309a14578ccb4b56aeed9e3e2674ddb37d4a4e07a384f54
- Size of remote file:
- 167 MB
- SHA256:
- 6f4091102ae7a58f2df9b88037b44fb8b269c775f9d92f7219f26cdb6a301902
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