Instructions to use prithivMLmods/SAT-Landforms-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/SAT-Landforms-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/SAT-Landforms-Classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/SAT-Landforms-Classifier") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/SAT-Landforms-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6d0d7c6dd0df50d83305b4f35c88d2263737235bf585465031239a5495ea252
- Size of remote file:
- 5.3 kB
- SHA256:
- ed979bb653d2b9283c87e896dc95c05c7a3f557031bc3df896f577bd7e15ca32
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.