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:
- 421a3ff8e610101e695e7b7c906cdd9b999acb1d71a3785b0db495fe35307f05
- Size of remote file:
- 737 kB
- SHA256:
- 6255e67ea1df4bda4ed17527f923f67c2c65d078a9178264c95173814e0abef5
路
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