Instructions to use karim155/convnext-tiny-224-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karim155/convnext-tiny-224-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="karim155/convnext-tiny-224-finetuned") 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("karim155/convnext-tiny-224-finetuned") model = AutoModelForImageClassification.from_pretrained("karim155/convnext-tiny-224-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24bd3506d4e5377971172fb26c7b07766ed28e42fc15faecc070d1d23a649c31
- Size of remote file:
- 5.18 kB
- SHA256:
- aa1349d9d70a279331b70954ea965b08839a1f45f203c6d867897af7eee21815
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.