Instructions to use aalonso-developer/vit-base-clothing-leafs-example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aalonso-developer/vit-base-clothing-leafs-example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="aalonso-developer/vit-base-clothing-leafs-example") 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("aalonso-developer/vit-base-clothing-leafs-example") model = AutoModelForImageClassification.from_pretrained("aalonso-developer/vit-base-clothing-leafs-example", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from aalonso-developer/vit-base-clothing-leafs-example: direct link, hf CLI and curl.
- Browser
- Download file 206 Bytes
-
https://huggingface.co/aalonso-developer/vit-base-clothing-leafs-example/resolve/main/eval_results.json
- Command line
-
hf download hf://aalonso-developer/vit-base-clothing-leafs-example/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/aalonso-developer/vit-base-clothing-leafs-example/resolve/main/eval_results.json
206 Bytes
| { | |
| "epoch": 5.0, | |
| "eval_accuracy": 0.044844754857893646, | |
| "eval_loss": 6.141994476318359, | |
| "eval_runtime": 145.3561, | |
| "eval_samples_per_second": 198.973, | |
| "eval_steps_per_second": 24.877 | |
| } |