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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35b039c0d18064671239f9f4f35fb6a5a57b88c2a9510d18925aae48756b0818
- Size of remote file:
- 31.2 MB
- SHA256:
- 5464ed9fe8671b3336d1e45c33523f53d79e3544f55ed1fd50a094872baf6cc8
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