Image Classification
Transformers
PyTorch
TensorBoard
English
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use stbnlen/pokemon_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stbnlen/pokemon_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="stbnlen/pokemon_classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("stbnlen/pokemon_classifier") model = AutoModelForImageClassification.from_pretrained("stbnlen/pokemon_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: pokemon_classifier
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results:
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- generated_from_trainer
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metrics:
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- accuracy
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widget:
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- src: https://datasets-server.huggingface.co/assets/keremberke/pokemon-classification/--/full/train/3/image/image.jpg
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example_title: Abra
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model-index:
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- name: pokemon_classifier
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results:
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