Image Classification
Transformers
TensorBoard
Safetensors
efficientnet
Generated from Trainer
Eval Results (legacy)
Instructions to use microwaveablemax/train_checkpoints2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microwaveablemax/train_checkpoints2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microwaveablemax/train_checkpoints2") 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("microwaveablemax/train_checkpoints2") model = AutoModelForImageClassification.from_pretrained("microwaveablemax/train_checkpoints2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- caa67698ea476ec2a420015f22cfac0cd446e87d70876fd9590df5e8be026af5
- Size of remote file:
- 5.3 kB
- SHA256:
- d772dae5aad1c84a42616151e1086497ef9a60754f6f9ddc7f9e82fc5fa997c8
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