Instructions to use JLei/climate_fever_roberta-base-fact-checking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JLei/climate_fever_roberta-base-fact-checking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JLei/climate_fever_roberta-base-fact-checking")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JLei/climate_fever_roberta-base-fact-checking") model = AutoModelForSequenceClassification.from_pretrained("JLei/climate_fever_roberta-base-fact-checking") - Notebooks
- Google Colab
- Kaggle
How to use your model?
#1
by fzanartu - opened
Hi!,
I'm really interested in trying out your model and wanted to ask a few questions:
- How do you typically pass the claim and evidence pairs? Do you use a specific separator like [SEP], , or another method?
- What tokenizer do you use for your model?
- Could you clarify the meaning of the labels LABEL_0, LABEL_1, and LABEL_2?
Thanks in advance!