Instructions to use SNV/bert-ner-custom_custom_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SNV/bert-ner-custom_custom_data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SNV/bert-ner-custom_custom_data")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SNV/bert-ner-custom_custom_data") model = AutoModelForTokenClassification.from_pretrained("SNV/bert-ner-custom_custom_data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("SNV/bert-ner-custom_custom_data")
model = AutoModelForTokenClassification.from_pretrained("SNV/bert-ner-custom_custom_data", device_map="auto")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SNV/bert-ner-custom_custom_data")