Text Classification
Transformers
Safetensors
roberta
devign
defect detection
code
Eval Results (legacy)
text-embeddings-inference
Instructions to use claudios/VulBERTa-MLP-Devign with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use claudios/VulBERTa-MLP-Devign with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="claudios/VulBERTa-MLP-Devign")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("claudios/VulBERTa-MLP-Devign") model = AutoModelForSequenceClassification.from_pretrained("claudios/VulBERTa-MLP-Devign") - Notebooks
- Google Colab
- Kaggle
Update tokenizer_config.json
Browse files- tokenizer_config.json +2 -2
tokenizer_config.json
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}
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},
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"clean_up_tokenization_spaces": true,
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"max_length":
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"model_max_length":
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"pad_to_multiple_of": null,
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"pad_token": "<pad>",
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"pad_token_type_id": 0,
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}
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},
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"clean_up_tokenization_spaces": true,
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"max_length": 1026,
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"model_max_length": 1026,
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"pad_to_multiple_of": null,
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"pad_token": "<pad>",
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"pad_token_type_id": 0,
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