Instructions to use CountingMstar/AI-Tutor-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CountingMstar/AI-Tutor-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="CountingMstar/AI-Tutor-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("CountingMstar/AI-Tutor-BERT") model = AutoModelForQuestionAnswering.from_pretrained("CountingMstar/AI-Tutor-BERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30403ad4a4cec88cb820fb101617d4095c63c3b2241d4e5ce97532396670b7d8
- Size of remote file:
- 436 MB
- SHA256:
- ecee135eb1b64a7c69c01d2c5af089ae4046f4270313f74808e89831b39e6827
路
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