Instructions to use johannes-garstenauer/distilbert-heaps-class3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use johannes-garstenauer/distilbert-heaps-class3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="johannes-garstenauer/distilbert-heaps-class3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("johannes-garstenauer/distilbert-heaps-class3") model = AutoModelForSequenceClassification.from_pretrained("johannes-garstenauer/distilbert-heaps-class3") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Trained on 5% of 'structs_token_size_4_pd_False_reduced_labelled' for 10 epochs.
Foundation model: 'distilbert-heaps-masked'
Training time: 19h
Eval Loss: 0.133 (pretty stable from the first epoch on)
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