Text Classification
Transformers
Safetensors
bert
bug-localization
code
r4
repositories
repository-library
research-library
t4_repo
text-embeddings-inference
Instructions to use PeytonT/bug-localization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PeytonT/bug-localization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PeytonT/bug-localization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PeytonT/bug-localization") model = AutoModelForSequenceClassification.from_pretrained("PeytonT/bug-localization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd7de7f2774aeedbda5a5bf895994ee5c724da8d280e9c7e4da9259e54fb7d58
- Size of remote file:
- 5.78 kB
- SHA256:
- 73c3a461e3ba2faf007cf1e1a4b4dbacf3ad73530048f577026aed3bb7e7730b
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