Text Classification
Transformers
PyTorch
JAX
roberta
code_x_glue_cc_defect_detection
code
security
vulnerability-detection
codebert
apache-2.0
Instructions to use mangsense/codebert_java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mangsense/codebert_java with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mangsense/codebert_java")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mangsense/codebert_java") model = AutoModelForSequenceClassification.from_pretrained("mangsense/codebert_java") - Notebooks
- Google Colab
- Kaggle
| {"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "sep_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "cls_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "model_max_length": 512, "special_tokens_map_file": "/root/.cache/torch/transformers/5a191080da4f00859b5d3d29529f57894583e00ab07b7c940d65c33db4b25d4d.16f949018cf247a2ea7465a74ca9a292212875e5fd72f969e0807011e7f192e4", "tokenizer_file": null, "name_or_path": "microsoft/codebert-base"} |