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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8fc93253137803eb78dc450ff48233c6224098c543f59b0be0efb626820a67e
- Size of remote file:
- 440 MB
- SHA256:
- 6f51749468b4c4919545963b5570753aeda595f22e32ceb72a2f1f33039d2a65
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