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
Fix pipeline tag, correct metadata typo, and add paper link
#1
by nielsr HF Staff - opened
Fixes the pipeline tag to image-text-to-text so the model can be found at https://huggingface.co/models?pipeline_tag=image-text-to-text&sort=trending.
Corrects the typo licence to license in the metadata and adds a link to the paper.