Instructions to use candra/base-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use candra/base-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="candra/base-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("candra/base-sentiment") model = AutoModelForSequenceClassification.from_pretrained("candra/base-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e5d453067d5cf1d5fee435b15b16082c29a3a324565fc69f0de7aa77c00600b
- Size of remote file:
- 5.24 kB
- SHA256:
- f95caa74b76225e1be7ecd38cf4a6eab7f0a18ae84bfbc52bdb97d3342854c56
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