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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mangsense/codebert_java") model = AutoModelForSequenceClassification.from_pretrained("mangsense/codebert_java", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from mangsense/codebert_java: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/mangsense/codebert_java/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://mangsense/codebert_java@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/mangsense/codebert_java/resolve/refs%2Fpr%2F1/model.safetensors
499 MB
- Xet hash:
- 1a2f2dda5b458f826ae644a96cdb1352e628c98ef2c41e8149ba9b47c6869e76
- Size of remote file:
- 499 MB
- SHA256:
- e5a29dca5d7654dc05527d544c377e62d35e36fb15f141ae6ba00e8a2a6a1574
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