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")# pip install -U transformers accelerate # 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 names/tokenizer.json from SlayerLab/NERGAL: direct link, hf CLI and curl.
- Browser
- Download file 3.69 MB
-
https://huggingface.co/SlayerLab/NERGAL/resolve/main/names/tokenizer.json
- Command line
-
hf download hf://SlayerLab/NERGAL/names/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SlayerLab/NERGAL/resolve/main/names/tokenizer.json
3.69 MB
- Xet hash:
- 3655edd7c81bfe995bcf4ddc5e26352079e2e453e0edd559912627897bc77d6b
- Size of remote file:
- 3.69 MB
- SHA256:
- 3a690c2d605076ad3901d946d4c0145fbfb19fef2f01370c7388430aa9f31edf
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