Instructions to use tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000") 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("tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000") model = AutoModelForImageClassification.from_pretrained("tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,417 Bytes
aa79212 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | [2026-01-05 22:18:56,613][fusion_bench.programs.fusion_program][INFO] - Running the model fusion program.
[2026-01-05 22:18:56,616][fusion_bench.programs.fusion_program][INFO] - loading model pool
[2026-01-05 22:18:59,043][fusion_bench.programs.fusion_program][INFO] - loading method
[2026-01-05 22:18:59,108][fusion_bench.method.classification.image_classification_finetune][INFO] - Training interval: step
[2026-01-05 22:18:59,109][fusion_bench.method.classification.image_classification_finetune][INFO] - Max epochs: -1, max steps: 4000
[2026-01-05 22:18:59,110][fusion_bench.programs.fusion_program][INFO] - loading task pool
[2026-01-05 22:19:01,585][fusion_bench.method.classification.image_classification_finetune][INFO] - Number of classes for dataset resisc45: 45
[2026-01-05 22:19:05,201][fusion_bench.method.classification.image_classification_finetune][INFO] - Training dataset size: 18900
[2026-01-05 22:19:07,683][fusion_bench.method.classification.image_classification_finetune][INFO] - optimizer:
SGD (
Parameter Group 0
dampening: 0
differentiable: False
foreach: None
fused: None
lr: 0.01
maximize: False
momentum: 0.9
nesterov: False
weight_decay: 0.0001
)
[2026-01-05 22:58:09,348][fusion_bench.method.classification.image_classification_finetune][INFO] - Saving the final model to outputs/convnext-base-224/resisc45/batch_size=64,lr=0.01/raw_checkpoints/final
|