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
- Xet hash:
- c441e3af272f48ab7dee6b4ccd7f037a7de1e7f229317084dd30cf7b2778b0ec
- Size of remote file:
- 17.1 MB
- SHA256:
- a54cb01d8728aea3cca3f62eac3940b59b564193f41b548a1e03bb59da22acee
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