Instructions to use 96harsh56/bert_test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 96harsh56/bert_test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="96harsh56/bert_test1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("96harsh56/bert_test1") model = AutoModelForQuestionAnswering.from_pretrained("96harsh56/bert_test1") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3 opened over 1 year ago
by
SFconvertbot
Add evaluation results on the default config and train split of social_i_qa
#2 opened over 2 years ago
by
autoevaluator
Add evaluation results on the adversarialQA config and validation split of adversarial_qa
#1 opened about 3 years ago
by
autoevaluator