Instructions to use mikga/pattern1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikga/pattern1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mikga/pattern1") 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/pattern1") model = AutoModelForImageClassification.from_pretrained("mikga/pattern1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 0
Browse files
pytorch_model.bin
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runs/Sep04_23-11-00_isei20230630-1255-hang/events.out.tfevents.1693887067.isei20230630-1255-hang.3011631.0
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runs/Sep05_19-21-07_isei20230630-1255-hang/events.out.tfevents.1693959674.isei20230630-1255-hang.2349074.0
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training_args.bin
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