Instructions to use fe1nt/detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fe1nt/detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="fe1nt/detr")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("fe1nt/detr") model = AutoModelForObjectDetection.from_pretrained("fe1nt/detr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fe1nt/detr: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/fe1nt/detr/resolve/main/training_args.bin
- Command line
-
hf download hf://fe1nt/detr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fe1nt/detr/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 8cc80866c227237bdf8732a91ace877693fe1c2f7b6ef14d564ea49aa6fc57ce
- Size of remote file:
- 4.98 kB
- SHA256:
- 7159e7e1dd729e8f108d763421204bafb6dd03ac986d1bb50b45dd1a45e74ef9
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