Instructions to use LucasS/robertaABSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LucasS/robertaABSA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="LucasS/robertaABSA")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("LucasS/robertaABSA") model = AutoModelForQuestionAnswering.from_pretrained("LucasS/robertaABSA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1ee10b0b4678acfd1cc7fd82b65e8f12fc67777fed682d261fabb129631e6e1
- Size of remote file:
- 496 MB
- SHA256:
- 44732529ea7a2fd6dfcffceb3e90d7d29abed88ccc7c5ac64c963d61d51058eb
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