Instructions to use KevSun/climate-attitude-LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KevSun/climate-attitude-LM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KevSun/climate-attitude-LM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KevSun/climate-attitude-LM") model = AutoModelForSequenceClassification.from_pretrained("KevSun/climate-attitude-LM") - Notebooks
- Google Colab
- Kaggle
Add model binary and training arguments
Browse files- merges.txt +0 -0
- pytorch_model.bin +3 -0
- tokenizer.json +0 -0
- training_args.bin +3 -0
merges.txt
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pytorch_model.bin
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oid sha256:7bc667f5dc8fa76226a9a59d1e2d461696db4dd0e27ca5e29b12c2706ab923fa
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tokenizer.json
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training_args.bin
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oid sha256:3dc6dd207207ad9bc50d392740f682bc13a3a46f813b11ef71061a884a491e07
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size 4344
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