Instructions to use SlayerLab/NERGAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SlayerLab/NERGAL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SlayerLab/NERGAL")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SlayerLab/NERGAL") model = AutoModelForTokenClassification.from_pretrained("SlayerLab/NERGAL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download figures/primary-three-model-curves.png from SlayerLab/NERGAL: direct link, hf CLI and curl.
- Browser
- Download file 177 kB
-
https://huggingface.co/SlayerLab/NERGAL/resolve/7b7f961957267e4439c13c67c51b634fd7fbc76b/figures/primary-three-model-curves.png
- Command line
-
hf download hf://SlayerLab/NERGAL@7b7f961957267e4439c13c67c51b634fd7fbc76b/figures/primary-three-model-curves.png
-
curl -L -o primary-three-model-curves.png https://huggingface.co/SlayerLab/NERGAL/resolve/7b7f961957267e4439c13c67c51b634fd7fbc76b/figures/primary-three-model-curves.png
177 kB

- Xet hash:
- 2070cd64cf730bde3fc8f4f31f7add799e933945cfe0e8e2db38aad9e850a8ac
- Size of remote file:
- 177 kB
- SHA256:
- c84b632606f398fc49b2289cc13d22c5ec6481cb6fcf147fdf0a315e46053deb
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