Instructions to use prachuryyaIITG/CLASSER_Nepali_MuRIL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prachuryyaIITG/CLASSER_Nepali_MuRIL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="prachuryyaIITG/CLASSER_Nepali_MuRIL")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("prachuryyaIITG/CLASSER_Nepali_MuRIL") model = AutoModelForTokenClassification.from_pretrained("prachuryyaIITG/CLASSER_Nepali_MuRIL") - Notebooks
- Google Colab
- Kaggle
Add library_name to metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the community science team at Hugging Face.
This PR adds library_name: transformers to the model card's metadata. This will enable the "Use in Transformers" button on the model page, helping users quickly load and use your model with the standard library.
The model card already provides excellent documentation, including performance metrics, sample usage, and links to the paper and GitHub repository!
prachuryyaIITG changed pull request status to merged