Instructions to use sethkimmel3/distilbert-aviation-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sethkimmel3/distilbert-aviation-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sethkimmel3/distilbert-aviation-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sethkimmel3/distilbert-aviation-classification") model = AutoModelForSequenceClassification.from_pretrained("sethkimmel3/distilbert-aviation-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
This is a simple binary text classification model, fine-tuned on distilbert to determine whether or not a block of text is or is not related to aviation. It was fine-tuned using the ASRS and cc_news datasets. You can view the notebook used for fine-tuning here.
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