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 sentencepiece.bpe.model from SlayerLab/NERGAL: direct link, hf CLI and curl.
- Browser
- Download file 5.07 MB
-
https://huggingface.co/SlayerLab/NERGAL/resolve/7b7f961957267e4439c13c67c51b634fd7fbc76b/sentencepiece.bpe.model
- Command line
-
hf download hf://SlayerLab/NERGAL@7b7f961957267e4439c13c67c51b634fd7fbc76b/sentencepiece.bpe.model
-
curl -L -o sentencepiece.bpe.model https://huggingface.co/SlayerLab/NERGAL/resolve/7b7f961957267e4439c13c67c51b634fd7fbc76b/sentencepiece.bpe.model
5.07 MB
- Xet hash:
- ad3e6aac23a8a87f79c4164f1ce17d9d5bbbd51e8edd05bd00e3d06dd9e802a8
- Size of remote file:
- 5.07 MB
- SHA256:
- cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
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