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:
- c53c0b14028c45abbbaad5566e2c8481b0c204e83c515ec3207431d1721e1aae
- Size of remote file:
- 3.9 kB
- SHA256:
- 77e36a9b38e6c71ebd9cb2b5fd02e57bc610b7355d86aa7c5508be220e04da00
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