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:
- 702f4ef8ac6c573e4b010fc7d49e7dc472d1e411bed91c70968a2c30fbcaca41
- Size of remote file:
- 5.18 kB
- SHA256:
- c9c0b9ab6dfebb39d810b30a0366b4a109b584f23b8e261b85f9b572790a75ee
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