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:
- 296ab33655a82a7db781536cfe2cfb704b8b1547fd1cbf50a2f95da2ee91e764
- Size of remote file:
- 329 MB
- SHA256:
- 367a588305d16523ff929e23cd1ca682615b909cf0b117e4b8f9070fdd98eb81
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