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 # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="96harsh56/bert_test1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("96harsh56/bert_test1") model = AutoModelForQuestionAnswering.from_pretrained("96harsh56/bert_test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
autoevaluator HF Staff
Add evaluation results on the default config and train split of social_i_qa
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