Instructions to use dexforint/train_result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dexforint/train_result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="dexforint/train_result")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("dexforint/train_result") model = AutoModelForObjectDetection.from_pretrained("dexforint/train_result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 8100
Browse files
pytorch_model.bin
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runs/Jun12_08-31-14_765124b5b6b2/events.out.tfevents.1686558761.765124b5b6b2.23.0
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