Instructions to use MutazYoune/Absa_AspectSentiment_hotels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MutazYoune/Absa_AspectSentiment_hotels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MutazYoune/Absa_AspectSentiment_hotels")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MutazYoune/Absa_AspectSentiment_hotels") model = AutoModelForSequenceClassification.from_pretrained("MutazYoune/Absa_AspectSentiment_hotels") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b9eeea397257d4c2f2f8d214f91da3e8f567985a068ab1d4bbb1b07b598fd38
- Size of remote file:
- 436 MB
- SHA256:
- e338ae07e995aa82e0201531ac46483ffc26a963b3f43aa6595c8d93fec216f3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.