Instructions to use jvadlamudi2/convnext-tiny-224-jvadlamudi2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jvadlamudi2/convnext-tiny-224-jvadlamudi2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jvadlamudi2/convnext-tiny-224-jvadlamudi2") 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("jvadlamudi2/convnext-tiny-224-jvadlamudi2") model = AutoModelForImageClassification.from_pretrained("jvadlamudi2/convnext-tiny-224-jvadlamudi2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 387 Bytes
ede3aed db849d8 555f0cd ede3aed | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"epoch": 3.0,
"eval_accuracy": 0.6160714285714286,
"eval_loss": 0.6697055697441101,
"eval_runtime": 0.8467,
"eval_samples_per_second": 132.281,
"eval_steps_per_second": 4.724,
"total_flos": 6.716617754447462e+16,
"train_loss": 0.630237170628139,
"train_runtime": 87.2731,
"train_samples_per_second": 30.628,
"train_steps_per_second": 0.241
} |