Instructions to use HorcruxNo13/beit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/beit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/beit-base-patch16-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("HorcruxNo13/beit-base-patch16-224") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/beit-base-patch16-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- all_results.json +8 -0
- train_results.json +8 -0
- trainer_state.json +516 -0
all_results.json
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{
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"epoch": 36.0,
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"total_flos": 1.2659877490145034e+18,
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"train_loss": 0.10912525819407569,
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"train_runtime": 949.2365,
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"train_samples_per_second": 21.523,
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"train_steps_per_second": 0.095
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}
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train_results.json
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{
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"epoch": 36.0,
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"total_flos": 1.2659877490145034e+18,
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"train_loss": 0.10912525819407569,
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"train_runtime": 949.2365,
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"train_samples_per_second": 21.523,
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"train_steps_per_second": 0.095
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}
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trainer_state.json
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|
| 1 |
+
{
|
| 2 |
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| 3 |
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| 4 |
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|
| 5 |
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