Instructions to use prachuryyaIITG/CLASSER_Bodo_MuRIL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prachuryyaIITG/CLASSER_Bodo_MuRIL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="prachuryyaIITG/CLASSER_Bodo_MuRIL")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("prachuryyaIITG/CLASSER_Bodo_MuRIL") model = AutoModelForTokenClassification.from_pretrained("prachuryyaIITG/CLASSER_Bodo_MuRIL") - Notebooks
- Google Colab
- Kaggle
Add library_name and project links
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
I've opened this PR to improve the metadata and documentation for this model. Specifically:
- Added
library_name: transformersto the metadata to enable automated code snippets and the inference widget. - Included direct links to the AWED-FiNER research paper and GitHub repository in the model card for better discoverability.
- Formatted the existing performance and training information for better readability.
These changes help users understand the context of the model as part of the AWED-FiNER collection and make it easier to use within the Hugging Face ecosystem.
prachuryyaIITG changed pull request status to merged