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:
- 8e0608daf94aee87d0c6ead1e56dad33f8e1bbbfb8c309dc9db2c466ef439272
- Size of remote file:
- 3.77 kB
- SHA256:
- 9fb8a85439cb6002bb223a0a18630ff6d734d92e4e8b0b033115c8b11632ab11
路
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