Instructions to use driftbench/climateattention-10k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use driftbench/climateattention-10k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="driftbench/climateattention-10k")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("driftbench/climateattention-10k") model = AutoModelForSequenceClassification.from_pretrained("driftbench/climateattention-10k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3b55c71024b09976f410c69f6d88af6e1a4f3cff2113a8e3aa583eec256546d
- Size of remote file:
- 3.45 kB
- SHA256:
- 6c196d389f8bad89c383025c54802ad063b8923260e80f98bf5bca16f7995090
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