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 # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="Tami3/HazardNet")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Tami3/HazardNet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Tami3/HazardNet: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Tami3/HazardNet/resolve/main/tokenizer.json
- Command line
-
hf download hf://Tami3/HazardNet/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Tami3/HazardNet/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 4b00656bad4d9a1a30747ba1c640b2e9c41e8a26349aedc04571c21fce74f8bb
- Size of remote file:
- 11.4 MB
- SHA256:
- 948c45c29a91dd2e6ae77d6f5a324a3d408bcca6ad443365b2e79986f1422771
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