Instructions to use SRDdev/QABERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/QABERT-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="SRDdev/QABERT-small")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SRDdev/QABERT-small") model = AutoModelForQuestionAnswering.from_pretrained("SRDdev/QABERT-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51e1548a0de73fae442d0485bc635fba8b55c2b77a1d577dadc84e1eb9aebcbe
- Size of remote file:
- 265 MB
- SHA256:
- e6cf53ada81236b3988e49e4c5e41e0cf7add596f5a4c0156f2bc8a16be22d34
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