Instructions to use climatebert/distilroberta-base-climate-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use climatebert/distilroberta-base-climate-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="climatebert/distilroberta-base-climate-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("climatebert/distilroberta-base-climate-sentiment") model = AutoModelForSequenceClassification.from_pretrained("climatebert/distilroberta-base-climate-sentiment") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68f61317c04de88cadae4e98937be0973d70604eeb7b849eb5d5073c7492a571
- Size of remote file:
- 329 MB
- SHA256:
- 72bbbf38260e508b868cd0571ff1aceb9b802ee52cb58606f0d4f96feb1eb234
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