Instructions to use William0609/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use William0609/trained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="William0609/trained_model")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("William0609/trained_model") model = AutoModelForObjectDetection.from_pretrained("William0609/trained_model") - Notebooks
- Google Colab
- Kaggle
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update model card README.md
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README.md
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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# trained_model
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This model
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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### Training results
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---
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tags:
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- generated_from_trainer
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datasets:
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# trained_model
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This model was trained from scratch on the imagefolder dataset.
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 200
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### Training results
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