Instructions to use nasa-impact/division-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nasa-impact/division-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nasa-impact/division-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nasa-impact/division-classifier") model = AutoModelForSequenceClassification.from_pretrained("nasa-impact/division-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5181b4224eb5db32e3eeed832f7dbb86af7b094b627b52441c9b1a76d85a30fc
- Size of remote file:
- 5.05 kB
- SHA256:
- 4b889d341dc91f04dd5979228309dc7d193954e9e40e8521606169334bf499f2
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