Instructions to use jfernsler/ASRS_distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jfernsler/ASRS_distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jfernsler/ASRS_distilbert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jfernsler/ASRS_distilbert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("jfernsler/ASRS_distilbert-base-uncased") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
Finetuned distilbert for classifying ASRS data.
Model Details
Model Description
This is a distilbert-base-uncased fine tuned to classify Aviation Safety Reporting System (ASRS) into 15 different categories. The categories are unlabeled an are based on clustering ASRS anomaly reports. More work would need to be done to add context to the clusters.
- Developed by: Jeremy Fernsler
- Model type: distilbert classifier
- Language(s) (NLP): English
- Finetuned from model [optional]: distilbert-base-uncased
Model Sources
- Repository: https://github.com/jfernsler/ASRS_Classifier
Uses
Classifying Aviation Safety Reporting System narratives into easily identifiable classes.
How to Get Started with the Model
Get some ASRS narratives and see where they land!
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