Text Classification
Transformers
Safetensors
roberta
code-defect-detection
c
text-embeddings-inference
Instructions to use lafarizo/code_defect_detection_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lafarizo/code_defect_detection_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lafarizo/code_defect_detection_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lafarizo/code_defect_detection_v1") model = AutoModelForSequenceClassification.from_pretrained("lafarizo/code_defect_detection_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89a69c43d9a6b84e0fd4779c2f5c94b52f552f807269b26cd78f44df12494f4e
- Size of remote file:
- 499 MB
- SHA256:
- 2e704e3eac1797a0176e5ff56135c63a869fa4b9574bff939a33dd41106fbddb
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