Instructions to use gary2002/output_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gary2002/output_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gary2002/output_dir") 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("gary2002/output_dir") model = AutoModelForImageClassification.from_pretrained("gary2002/output_dir") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- all_results.json +8 -0
- model.safetensors +1 -1
- train_results.json +8 -0
all_results.json
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{
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"epoch": 3.0,
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"total_flos": 1.6948561394167603e+17,
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"train_loss": 1.5463701361390554,
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"train_runtime": 160.3132,
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"train_samples_per_second": 13.642,
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"train_steps_per_second": 1.366
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 343245508
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version https://git-lfs.github.com/spec/v1
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oid sha256:0f78deca653a2f2cefec99bdd9a3a2d341587c4f27da7775c02b2e722f42dfa3
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size 343245508
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train_results.json
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{
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"epoch": 3.0,
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"total_flos": 1.6948561394167603e+17,
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"train_loss": 1.5463701361390554,
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"train_runtime": 160.3132,
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"train_samples_per_second": 13.642,
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"train_steps_per_second": 1.366
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}
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