Instructions to use l3cube-pune/marathi-question-answering-squad-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-question-answering-squad-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="l3cube-pune/marathi-question-answering-squad-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-question-answering-squad-bert") model = AutoModelForQuestionAnswering.from_pretrained("l3cube-pune/marathi-question-answering-squad-bert") - Notebooks
- Google Colab
- Kaggle
Improve model card with pipeline tag and library name
#1
by nielsr HF Staff - opened
This PR improves the model card by adding the pipeline_tag and library_name metadata, ensuring better discoverability and usability on the Hugging Face Hub. This also ensures the "How to use" button is correctly displayed.
Thanks!
l3cube-pune changed pull request status to merged