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
Download pipeline_verification/tfidf_training_verification.json from bengoldberg0/granite-4.2-3b-phishing-url-qlora: direct link, hf CLI and curl.
- Browser
- Download file 860 Bytes
-
https://huggingface.co/bengoldberg0/granite-4.2-3b-phishing-url-qlora/resolve/main/pipeline_verification/tfidf_training_verification.json
- Command line
-
hf download hf://bengoldberg0/granite-4.2-3b-phishing-url-qlora/pipeline_verification/tfidf_training_verification.json
-
curl -L -o tfidf_training_verification.json https://huggingface.co/bengoldberg0/granite-4.2-3b-phishing-url-qlora/resolve/main/pipeline_verification/tfidf_training_verification.json
860 Bytes
| { | |
| "checks": [ | |
| { | |
| "benchmark": "validation", | |
| "examples": 400, | |
| "prediction_disagreements": 0, | |
| "maximum_absolute_score_difference": 1.1102230246251565e-16 | |
| }, | |
| { | |
| "benchmark": "internal", | |
| "examples": 400, | |
| "prediction_disagreements": 0, | |
| "maximum_absolute_score_difference": 1.1102230246251565e-16 | |
| }, | |
| { | |
| "benchmark": "published", | |
| "examples": 500, | |
| "prediction_disagreements": 0, | |
| "maximum_absolute_score_difference": 1.1102230246251565e-16 | |
| }, | |
| { | |
| "benchmark": "external", | |
| "examples": 500, | |
| "prediction_disagreements": 0, | |
| "maximum_absolute_score_difference": 1.1102230246251565e-16 | |
| } | |
| ], | |
| "all_predictions_match": true, | |
| "scope": "Refactored TF-IDF training compared with original saved validation and test predictions. No tuning performed." | |
| } |