Instructions to use natriistorm/DeepPavlov-ABSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use natriistorm/DeepPavlov-ABSA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="natriistorm/DeepPavlov-ABSA")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("natriistorm/DeepPavlov-ABSA") model = AutoModelForTokenClassification.from_pretrained("natriistorm/DeepPavlov-ABSA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ac4706cc3c90313627b45bc62e236777b117bb725050d0c71deb8f507d9d7e0
- Size of remote file:
- 17.1 MB
- SHA256:
- 8a3d8b13e81f1324c05ee2a010c2f9b49f4ceb5887da444843b6dddd035d8701
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