Instructions to use prachuryyaIITG/MultiCoNER2_English_XLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prachuryyaIITG/MultiCoNER2_English_XLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="prachuryyaIITG/MultiCoNER2_English_XLM")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("prachuryyaIITG/MultiCoNER2_English_XLM") model = AutoModelForTokenClassification.from_pretrained("prachuryyaIITG/MultiCoNER2_English_XLM") - Notebooks
- Google Colab
- Kaggle
Add library_name and improve metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community science team. I noticed that this model is part of the AWED-FiNER project and is compatible with the transformers library.
I've opened this PR to:
- Add
library_name: transformersto the metadata to enable the "Use in Transformers" button and automated code snippets. - Maintain the
token-classificationpipeline tag for better discoverability. - Ensure the paper and GitHub repository are clearly linked in the model card.
Thanks for your contribution to the community!
prachuryyaIITG changed pull request status to merged