Instructions to use arrafmousa/final_argument_manager with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arrafmousa/final_argument_manager with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="arrafmousa/final_argument_manager")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("arrafmousa/final_argument_manager") model = AutoModelForQuestionAnswering.from_pretrained("arrafmousa/final_argument_manager", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ef1e219ee425cde88c5e44f272e90aafd6cbe17d580616263af552e56d1bf25
- Size of remote file:
- 496 MB
- SHA256:
- e88e63209c7f6734eb89e8544c6c78c583003fe51b45fcdbb27084b51ab1f6c5
路
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