Text Classification
Transformers
PyTorch
English
roberta
fact-checking
climate
text entailment
text-embeddings-inference
Instructions to use amandakonet/climatebert-fact-checking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amandakonet/climatebert-fact-checking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amandakonet/climatebert-fact-checking")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amandakonet/climatebert-fact-checking") model = AutoModelForSequenceClassification.from_pretrained("amandakonet/climatebert-fact-checking") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e3eb454380fedc53bb741a3bb58c60e69905e598a14692feec1106696400eda
- Size of remote file:
- 329 MB
- SHA256:
- de1504f235581f68d3a83c99754e8359815ba1bbc5fa5b9bb7965a3e4106ab9e
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