Image Classification
Transformers
Safetensors
bit
LADI
Aerial Imagery
Disaster Response
Emergency Management
Instructions to use MITLL/LADI-v2-classifier-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MITLL/LADI-v2-classifier-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MITLL/LADI-v2-classifier-small") 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") model = AutoModelForImageClassification.from_pretrained("MITLL/LADI-v2-classifier-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cc5fca3aeabe8b6a6014bb11a9c4290a394df1c2be5353df4676aa66584ad29
- Size of remote file:
- 94.1 MB
- SHA256:
- 5ff777c9d1580eb5bd2f03d0dc5318bdfa77876d49ee1cda14ed70d9c3f47e76
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