Instructions to use susnato/detr-resnet-50_finetuned_plant_disease_detection_processed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use susnato/detr-resnet-50_finetuned_plant_disease_detection_processed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="susnato/detr-resnet-50_finetuned_plant_disease_detection_processed")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("susnato/detr-resnet-50_finetuned_plant_disease_detection_processed") model = AutoModelForObjectDetection.from_pretrained("susnato/detr-resnet-50_finetuned_plant_disease_detection_processed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 50
Browse files
README.md
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model-index:
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- name: detr-resnet-50_finetuned_plant_disease_detection_processed
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results: []
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---
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- Transformers 4.36.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.15.0
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model-index:
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- name: detr-resnet-50_finetuned_plant_disease_detection_processed
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.36.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.15.0
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model.safetensors
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runs/Nov26_03-10-59_susnato-desktop/events.out.tfevents.1700948461.susnato-desktop.27893.0
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training_args.bin
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