Instructions to use prachuryyaIITG/MultiCoNER2_Spanish_XLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prachuryyaIITG/MultiCoNER2_Spanish_XLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="prachuryyaIITG/MultiCoNER2_Spanish_XLM")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("prachuryyaIITG/MultiCoNER2_Spanish_XLM") model = AutoModelForTokenClassification.from_pretrained("prachuryyaIITG/MultiCoNER2_Spanish_XLM") - Notebooks
- Google Colab
- Kaggle
Add library_name to metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
I've opened this PR to add the library_name: transformers tag to your model card. This metadata helps users discover your model more easily and enables the "Use in Transformers" button on the model page, which provides a ready-to-use code snippet.
I have also ensured that the model is contextualized as part of the AWED-FiNER collection and properly references the associated research paper.
Please let me know if you have any questions!
prachuryyaIITG changed pull request status to merged