Text Classification
Transformers
Safetensors
English
bert
customer-feedback
aspect-based-sentiment-analysis
text-embeddings-inference
Instructions to use jiangzy1881/aspect-detection-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiangzy1881/aspect-detection-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jiangzy1881/aspect-detection-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jiangzy1881/aspect-detection-model") model = AutoModelForSequenceClassification.from_pretrained("jiangzy1881/aspect-detection-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bea47eea5e97a78178125df1e3d7b3822f012bece83b9ac149f1883b6dbfafa8
- Size of remote file:
- 5.2 kB
- SHA256:
- 13d33703ee2666b25a5e7af9e6c60dfcaf191c8071f2d9bed0d8d910b5afc307
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