Instructions to use l3cube-pune/telugu-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/telugu-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/telugu-question-answering-squad-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/telugu-question-answering-squad-bert") model = AutoModelForQuestionAnswering.from_pretrained("l3cube-pune/telugu-question-answering-squad-bert") - Notebooks
- Google Colab
- Kaggle
Improve model card: Correct pipeline tag, datasets link, base model and add library name
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Correcting the pipeline tag to
question-answering. - Correcting the base model to
l3cube-pune/telugu-bert. - Adding
library_name: transformers. - Correcting the link to the dataset to the Hugging Face Datasets page.
- Adding a more descriptive introduction section.
This ensures the model card is more informative and easier to use for other researchers.
Thanks!
l3cube-pune changed pull request status to merged