Instructions to use muhammadravi251001/DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muhammadravi251001/DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="muhammadravi251001/DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("muhammadravi251001/DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel") model = AutoModelForQuestionAnswering.from_pretrained("muhammadravi251001/DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a1e1102e8070ff3bdff90d6104b516f5b6dccaeb6bcbddfd3688727bbda3c5d
- Size of remote file:
- 440 MB
- SHA256:
- 7261e4bd1c9b8547699be56e6aa48c44c422873c866adbc265d8272204228322
路
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