Instructions to use mikga/pattern2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikga/pattern2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mikga/pattern2") 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("mikga/pattern2") model = AutoModelForImageClassification.from_pretrained("mikga/pattern2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
pytorch_model.bin
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runs/Oct04_03-02-03_isei20230630-1255-hang/events.out.tfevents.1696406527.isei20230630-1255-hang.85201.0
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runs/Oct04_19-40-27_isei20230630-1255-hang/events.out.tfevents.1696466431.isei20230630-1255-hang.85201.1
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training_args.bin
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