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
Update README.md
Browse files
README.md
CHANGED
|
@@ -9,7 +9,7 @@ pipeline_tag: image-classification
|
|
| 9 |
# Model Card for MITLL/LADI-v2-classifier-small-reference
|
| 10 |
LADI-v2-classifier-small-reference is based on [google/bit-50](https://huggingface.co/google/bit-50) and fine-tuned on the LADI v2_resized dataset. LADI-v2-classifier is trained to identify labels of interest to disaster response managers from aerial images.
|
| 11 |
|
| 12 |
-
This model is the 'reference' version of the model, which is trained on 80% of the 10,000 available images. It is provided to facilitate reproduction of our paper and is not intended to be used in deployment.
|
| 13 |
|
| 14 |
## Model Details
|
| 15 |
|
|
|
|
| 9 |
# Model Card for MITLL/LADI-v2-classifier-small-reference
|
| 10 |
LADI-v2-classifier-small-reference is based on [google/bit-50](https://huggingface.co/google/bit-50) and fine-tuned on the LADI v2_resized dataset. LADI-v2-classifier is trained to identify labels of interest to disaster response managers from aerial images.
|
| 11 |
|
| 12 |
+
🔴 __IMPORTANT__ ❗🔴 This model is the 'reference' version of the model, which is trained on 80% of the 10,000 available images. It is provided to facilitate reproduction of our paper and is not intended to be used in deployment.
|
| 13 |
|
| 14 |
## Model Details
|
| 15 |
|