Text Classification
Transformers
Safetensors
English
roberta
customer-feedback
aspect-based-sentiment-analysis
text-embeddings-inference
Instructions to use jiangzy1881/aspect-sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiangzy1881/aspect-sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jiangzy1881/aspect-sentiment-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jiangzy1881/aspect-sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("jiangzy1881/aspect-sentiment-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a4f98901be6600111f5336e11107dbb672a01bed4f1cb368dead6cf47be11cb
- Size of remote file:
- 5.2 kB
- SHA256:
- bde0afc164ed80a87b08fbbfa13051dcfdf4f82e9096de00ce7e112b36ad3f05
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