Instructions to use alvinmrrry837/detr-resnet-50-dc5-fashionpedia-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alvinmrrry837/detr-resnet-50-dc5-fashionpedia-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="alvinmrrry837/detr-resnet-50-dc5-fashionpedia-finetuned")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("alvinmrrry837/detr-resnet-50-dc5-fashionpedia-finetuned") model = AutoModelForObjectDetection.from_pretrained("alvinmrrry837/detr-resnet-50-dc5-fashionpedia-finetuned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c927e4c698a3b3c2f161f10fedefe779998a7c715d7581420274e4837b5be26
- Size of remote file:
- 167 MB
- SHA256:
- 6ce365a039fd28eb897c2ed8afbb975f735f58075fe6d7dea23dc78e53ffbce9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.