Instructions to use trtd56/practical_nlp_course_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trtd56/practical_nlp_course_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="trtd56/practical_nlp_course_5")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("trtd56/practical_nlp_course_5") model = AutoModelForQuestionAnswering.from_pretrained("trtd56/practical_nlp_course_5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c21df548f550f499fe2c871100329f9ab1d7623aa72946a8d39e7fdd4d8a141
- Size of remote file:
- 440 MB
- SHA256:
- 60df1bd56718cb4dcbe20b893dcde87673f580e6c8e267e63b59163be3c663ea
路
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