Token Classification
Transformers
Safetensors
English
deberta-v2
token classification
information extraction
NER
relation extraction
text cleaning
Instructions to use knowledgator/UTC-DeBERTa-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knowledgator/UTC-DeBERTa-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="knowledgator/UTC-DeBERTa-large-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("knowledgator/UTC-DeBERTa-large-v2") model = AutoModelForTokenClassification.from_pretrained("knowledgator/UTC-DeBERTa-large-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
training
#1
by ale-volpe - opened
Hello, nice work. May I ask how did you train this model? Do you have a sample notebook?
@ale-volpe , Hi, thank you! We trained it as a typical token classification model using Hugging Face trainer. I don't have a notebook to share, but I plan to prepare it in the near future. What can I recommend right now is to check this nice tutorial from Hugging Face.
Thank you so much, I appreciate your nice work and I will follow your progresses :)
Your models have great quality!
Keep up the good work
@ale-volpe , thank you! It will be good if you can share directions in which you are using our model. It will help us to understand in what we should invest our time more.