Instructions to use Chantland/HRAF_EVENT_Demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chantland/HRAF_EVENT_Demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Chantland/HRAF_EVENT_Demo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Chantland/HRAF_EVENT_Demo") model = AutoModelForSequenceClassification.from_pretrained("Chantland/HRAF_EVENT_Demo") - Notebooks
- Google Colab
- Kaggle
Text classification model used to decode passages that contain misfortunate events. Current F1 score of 140 passages not used for training is .94.
For a quick demo, try typing in a sentence or even a paragraph in the Hosted inference API then pressing "compute"!
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