Instructions to use Padu98/my_awesome_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Padu98/my_awesome_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Padu98/my_awesome_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Padu98/my_awesome_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Padu98/my_awesome_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c59c32c1454b28106327f4324e3c6689b2afa0c9e4d8877523ce0abf434fde4
- Size of remote file:
- 265 MB
- SHA256:
- 77ea5520dd6702a265ad90ce5b7bba7e1709509e808e92d79924e1225d67ec1b
路
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