Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Jiajing/SL_final_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jiajing/SL_final_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Jiajing/SL_final_model") 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("Jiajing/SL_final_model") model = AutoModelForImageClassification.from_pretrained("Jiajing/SL_final_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jiajing/SL_final_model: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Jiajing/SL_final_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jiajing/SL_final_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jiajing/SL_final_model/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- c0f63f16bcb6e7625d8971730de00d19506613d96e475a29c8ffc91dd82cb5e0
- Size of remote file:
- 343 MB
- SHA256:
- 01d4c9f78b21384a3a30599abcc3f661985122670b1a75c2f43cbdb7a59e7912
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