Instructions to use ronenlap/restaurants-48samples-AspectsExtraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ronenlap/restaurants-48samples-AspectsExtraction with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ronenlap/restaurants-48samples-AspectsExtraction") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - setfit
How to use ronenlap/restaurants-48samples-AspectsExtraction with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ronenlap/restaurants-48samples-AspectsExtraction") - Notebooks
- Google Colab
- Kaggle
Upload config_absasetfit.json with huggingface_hub
Browse files- config_absasetfit.json +1 -0
config_absasetfit.json
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{"seed": 42, "aspect_span": 0, "pretrained_ST_path": "sentence-transformers/paraphrase-mpnet-base-v2", "iter": 20, "epochs": 1, "batch_size": 4, "concat_sentence": true, "model_classes": ["ASP-N", "ASP-Y"], "lbl_cls_mapper": {"0": "ASP-N", "1": "ASP-Y"}, "isATE": true}
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