Image Classification
Transformers
Safetensors
swinv2
LADI
Aerial Imagery
Disaster Response
Emergency Management
Instructions to use MITLL/LADI-v2-classifier-large-reference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MITLL/LADI-v2-classifier-large-reference with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MITLL/LADI-v2-classifier-large-reference") 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("MITLL/LADI-v2-classifier-large-reference") model = AutoModelForImageClassification.from_pretrained("MITLL/LADI-v2-classifier-large-reference", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from MITLL/LADI-v2-classifier-large-reference: direct link, hf CLI and curl.
- Browser
- Download file 781 MB
-
https://huggingface.co/MITLL/LADI-v2-classifier-large-reference/resolve/main/model.safetensors
- Command line
-
hf download hf://MITLL/LADI-v2-classifier-large-reference/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/MITLL/LADI-v2-classifier-large-reference/resolve/main/model.safetensors
781 MB
- Xet hash:
- 71abb81e65d333c8f76b0706b132f4b585ae50f3c811cb143ae382b5cca8766e
- Size of remote file:
- 781 MB
- SHA256:
- c4fa0b95775666909dd2c40ee71366cb689c89c76932511bcf679aa6e5258a90
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