Instructions to use dslim/distilbert-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dslim/distilbert-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dslim/distilbert-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dslim/distilbert-NER") model = AutoModelForTokenClassification.from_pretrained("dslim/distilbert-NER") - Inference
- Notebooks
- Google Colab
- Kaggle
DistilBert-NER Inference using C++
#2
by aitechguy - opened
Named Entity Recognition (NER) is a crucial task in natural language processing that involves identifying and classifying named entities in text. I am going to implement inference DistilBert model using C++.
I would like to ask for help from someone with experience in this field.