Instructions to use Prience91/ner_model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prience91/ner_model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Prience91/ner_model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Prience91/ner_model_output") model = AutoModelForTokenClassification.from_pretrained("Prience91/ner_model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Prience91/ner_model_output: direct link, hf CLI and curl.
- Browser
- Download file 571 kB
-
https://huggingface.co/Prience91/ner_model_output/resolve/main/tokenizer.json
- Command line
-
hf download hf://Prience91/ner_model_output/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Prience91/ner_model_output/resolve/main/tokenizer.json
571 kB
File too large to display, you can check the raw version instead.