Instructions to use tanganke/convnext-base-224_dtd_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_dtd_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_dtd_sgd_batch-size-64_lr-0.01_steps-4000") 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("tanganke/convnext-base-224_dtd_sgd_batch-size-64_lr-0.01_steps-4000") model = AutoModelForImageClassification.from_pretrained("tanganke/convnext-base-224_dtd_sgd_batch-size-64_lr-0.01_steps-4000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,326 Bytes
5b7ffc0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | [2026-01-08 04:49:05,782][fusion_bench.programs.fusion_program][INFO] - Running the model fusion program.
[2026-01-08 04:49:05,785][fusion_bench.programs.fusion_program][INFO] - loading model pool
[2026-01-08 04:49:08,035][fusion_bench.programs.fusion_program][INFO] - loading method
[2026-01-08 04:49:08,098][fusion_bench.method.classification.image_classification_finetune][INFO] - Training interval: step
[2026-01-08 04:49:08,098][fusion_bench.method.classification.image_classification_finetune][INFO] - Max epochs: -1, max steps: 4000
[2026-01-08 04:49:08,099][fusion_bench.programs.fusion_program][INFO] - loading task pool
[2026-01-08 04:49:09,773][fusion_bench.method.classification.image_classification_finetune][INFO] - Number of classes for dataset dtd: 47
[2026-01-08 04:49:09,786][datasets.load][WARNING] - Using the latest cached version of the dataset since tanganke/dtd couldn't be found on the Hugging Face Hub (offline mode is enabled).
[2026-01-08 04:49:09,795][datasets.packaged_modules.cache.cache][WARNING] - Found the latest cached dataset configuration 'default' at /data/dataset/datasets/tanganke___dtd/default/0.0.0/d2afa97d9f335b1a6b3b09c637aef667f98f966e (last modified on Mon Jan 5 04:22:16 2026).
[2026-01-08 04:49:09,972][fusion_bench.method.classification.image_classification_finetune][INFO] - Training dataset size: 3760
[2026-01-08 04:49:10,003][datasets.load][WARNING] - Using the latest cached version of the dataset since tanganke/dtd couldn't be found on the Hugging Face Hub (offline mode is enabled).
[2026-01-08 04:49:10,010][datasets.packaged_modules.cache.cache][WARNING] - Found the latest cached dataset configuration 'default' at /data/dataset/datasets/tanganke___dtd/default/0.0.0/d2afa97d9f335b1a6b3b09c637aef667f98f966e (last modified on Mon Jan 5 04:22:16 2026).
[2026-01-08 04:49:10,060][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
)
[2026-01-08 05:15:05,827][fusion_bench.method.classification.image_classification_finetune][INFO] - Saving the final model to outputs/convnext-base-224/dtd/batch_size=64,lr=0.01/raw_checkpoints/final
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