Instructions to use cardiffnlp/bertweet-base-stance-climate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/bertweet-base-stance-climate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/bertweet-base-stance-climate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/bertweet-base-stance-climate") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/bertweet-base-stance-climate") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13f52c634522293f3865f8985532747b46e8deabd7450b2d99b6db3111543b92
- Size of remote file:
- 540 MB
- SHA256:
- 5f5c5db242dad2ddcd652477832f49862f92638d008950c49a0f6bd4203a4a4b
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