Instructions to use Alindstroem89/sentiment_model_testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alindstroem89/sentiment_model_testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Alindstroem89/sentiment_model_testing")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Alindstroem89/sentiment_model_testing") model = AutoModelForSequenceClassification.from_pretrained("Alindstroem89/sentiment_model_testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd0535e5071e9657a9a4d96aaca4e90727b03f4c0731b4ad6fd4cbad1dc7da14
- Size of remote file:
- 268 MB
- SHA256:
- c045be8f2d6569f188db014cc2299b2ea7d22c6cdd77d60b46f381562fe4899d
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