Instructions to use Tami3/HazardNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tami3/HazardNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Tami3/HazardNet")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Tami3/HazardNet", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5679b4dc99063ab504e98ed5f3b1c0119aae547427e87396710044f24000536e
- Size of remote file:
- 5.56 kB
- SHA256:
- 192dfba82b00d80e43a3bcb9824352292ce05220330a61558e1f3ec1fae4e988
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