Instructions to use ganbold13/roberta-base-ner-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ganbold13/roberta-base-ner-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ganbold13/roberta-base-ner-demo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ganbold13/roberta-base-ner-demo") model = AutoModelForTokenClassification.from_pretrained("ganbold13/roberta-base-ner-demo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ganbold13/roberta-base-ner-demo: direct link, hf CLI and curl.
- Browser
- Download file 3.85 MB
-
https://huggingface.co/ganbold13/roberta-base-ner-demo/resolve/main/tokenizer.json
- Command line
-
hf download hf://ganbold13/roberta-base-ner-demo/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ganbold13/roberta-base-ner-demo/resolve/main/tokenizer.json
3.85 MB
File too large to display, you can check the raw version instead.