Image Classification
Transformers
Safetensors
beit
knowledge_distillation
vision
Generated from Trainer
Instructions to use c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t3") 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("c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t3") model = AutoModelForImageClassification.from_pretrained("c14kevincardenas/beit-base-patch16-224_alpha0.7_temp5.0_t3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 631cfbbb6468901a9d453cc863dd0bc05fdaba0cf987b1a141f9433db5f84a67
- Size of remote file:
- 356 MB
- SHA256:
- 5cab88b24e65324aeb4f38bb484f17caee8bcc4a12ba774d0258ec37d94833db
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