Instructions to use LucasS/bertLargeABSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LucasS/bertLargeABSA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="LucasS/bertLargeABSA")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("LucasS/bertLargeABSA") model = AutoModelForQuestionAnswering.from_pretrained("LucasS/bertLargeABSA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37fcc91d9b37bb40d8a5626f03ee30b7c089ddcc114c55b2d5ba1c858917799b
- Size of remote file:
- 1.34 GB
- SHA256:
- 3bcf2825db744274b453a2f1a1119e95fc93d648822e3d0770605737889ec095
路
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