Instructions to use Etelis/Sentiment140_XLNET_5E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/Sentiment140_XLNET_5E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/Sentiment140_XLNET_5E")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/Sentiment140_XLNET_5E") model = AutoModelForSequenceClassification.from_pretrained("Etelis/Sentiment140_XLNET_5E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1089314c459a88fc8c29b7b14e436a613d1771cfdbd968cdfa3ac24a10ab7c33
- Size of remote file:
- 469 MB
- SHA256:
- e4e7e776b9a7db082d9f01d62b114511078dc5f3e9437a178b25b55fb587b211
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