Instructions to use Dzeniks/alberta_fact_checking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dzeniks/alberta_fact_checking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dzeniks/alberta_fact_checking")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dzeniks/alberta_fact_checking") model = AutoModelForSequenceClassification.from_pretrained("Dzeniks/alberta_fact_checking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
b39efcf
1
Parent(s): ca526ba
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (ef763985832065348796bd2bd553af73b8187873)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:703e122b28359b5268c87ed97b35016c00f796902b71cb455ad47e0d9f850d0b
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size 46748096
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