Instructions to use ajaypyatha/sdsqna with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajaypyatha/sdsqna with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ajaypyatha/sdsqna")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ajaypyatha/sdsqna") model = AutoModelForQuestionAnswering.from_pretrained("ajaypyatha/sdsqna", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19fbd57b29b051ef0ff83772603ca71d07a9811e6230d036cf4560a6a05955f9
- Size of remote file:
- 265 MB
- SHA256:
- c9e967ab95dd4b841479af4d31282413a54602eb58ee5a801324e7470416f657
路
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