Instructions to use bengoldberg0/granite-4.2-3b-phishing-url-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bengoldberg0/granite-4.2-3b-phishing-url-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ibm-granite/granite-4.2-3b") model = PeftModel.from_pretrained(base_model, "bengoldberg0/granite-4.2-3b-phishing-url-qlora") - Notebooks
- Google Colab
- Kaggle
Add query-string subset diagnostic
Browse files
README.md
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@@ -262,6 +262,28 @@ The published-subset advantage is larger at 10.6 points
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(-5.2 to 3.6), providing no clear accuracy advantage over TF-IDF.
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Only one training seed was evaluated.
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## Release verification
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The uploaded adapter and inference script were verified at revision
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(-5.2 to 3.6), providing no clear accuracy advantage over TF-IDF.
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Only one training seed was evaluated.
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### Query-string shortcut check
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No legitimate training examples contained query strings. To check
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whether gains were limited to flagging query-containing URLs, a
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post-hoc analysis compared models on test URLs without queries.
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- **Internal:** all 14 net additional correct predictions over TF-IDF
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came from URLs without queries. On this subset, QLoRA's accuracy
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advantage was 3.59 percentage points (95% paired-bootstrap interval:
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0.77 to 6.41).
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- **Published subset:** 50 of 53 net additional correct predictions
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over TF-IDF came from URLs without queries. The no-query advantage
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was 10.53 points (7.16 to 13.89).
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- **External:** no-query accuracy remained poor: 54.27% for QLoRA
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versus 55.77% for TF-IDF.
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Simply flagging query-containing test URLs cannot explain the
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familiar-source gains. This does not establish causal independence
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from query-related learning or rule out other shortcuts. Intervals
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use 5,000 paired, source/class-stratified bootstrap replicates and
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are not adjusted for multiple comparisons or training-seed variability.
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## Release verification
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The uploaded adapter and inference script were verified at revision
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