Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mcanoglu/microsoft-codebert-base-finetuned-defect-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcanoglu/microsoft-codebert-base-finetuned-defect-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mcanoglu/microsoft-codebert-base-finetuned-defect-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mcanoglu/microsoft-codebert-base-finetuned-defect-detection") model = AutoModelForSequenceClassification.from_pretrained("mcanoglu/microsoft-codebert-base-finetuned-defect-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from mcanoglu/microsoft-codebert-base-finetuned-defect-detection: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/mcanoglu/microsoft-codebert-base-finetuned-defect-detection/resolve/79f359dfeab0cda8bc3d5384f205ca4c8a746ead/tokenizer.json
- Command line
-
hf download hf://mcanoglu/microsoft-codebert-base-finetuned-defect-detection@79f359dfeab0cda8bc3d5384f205ca4c8a746ead/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mcanoglu/microsoft-codebert-base-finetuned-defect-detection/resolve/79f359dfeab0cda8bc3d5384f205ca4c8a746ead/tokenizer.json
2.11 MB
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