Instructions to use prachuryyaIITG/MultiCoNER2_Italian_XLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prachuryyaIITG/MultiCoNER2_Italian_XLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="prachuryyaIITG/MultiCoNER2_Italian_XLM")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("prachuryyaIITG/MultiCoNER2_Italian_XLM") model = AutoModelForTokenClassification.from_pretrained("prachuryyaIITG/MultiCoNER2_Italian_XLM") - Notebooks
- Google Colab
- Kaggle
Add library_name and improve documentation
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
This PR improves the model card by adding the library_name: transformers metadata. This ensures that the "Use in Transformers" button appears on the model page, providing users with a ready-to-use code snippet to load the model. I've also added a brief introduction linking this expert detector to the AWED-FiNER paper and collection.
Feel free to merge if this looks good to you!
prachuryyaIITG changed pull request status to merged