Instructions to use LucasS/albertABSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LucasS/albertABSA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="LucasS/albertABSA")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("LucasS/albertABSA") model = AutoModelForQuestionAnswering.from_pretrained("LucasS/albertABSA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bceb9dcc497cbfd48c411fa4388fb3e88b2d571e68a4bb1f686bedd480e4569
- Size of remote file:
- 44.4 MB
- SHA256:
- 377d2e43284a5d10423909508f49a8b304a44b2bbfaf371dac410b347cf8b67a
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