Image Classification
Transformers
Safetensors
bit
LADI
Aerial Imagery
Disaster Response
Emergency Management
Instructions to use MITLL/LADI-v2-classifier-small-reference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MITLL/LADI-v2-classifier-small-reference with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MITLL/LADI-v2-classifier-small-reference") 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("MITLL/LADI-v2-classifier-small-reference") model = AutoModelForImageClassification.from_pretrained("MITLL/LADI-v2-classifier-small-reference") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f7d8587a50c7e6432ea2f3dd992f11f310aa992a7a7cd215cbbd19eff429159
- Size of remote file:
- 94.1 MB
- SHA256:
- 57288c631557ec80d9d50e4f4b7f5b11aeb1c3fd9905fc3c6c6d59e7cbf45213
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