Instructions to use rootxhacker/CodeAstra-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rootxhacker/CodeAstra-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "rootxhacker/CodeAstra-7B") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -27,7 +27,7 @@ CodeAstra-7b is a state-of-the-art language model fine-tuned for vulnerability d
|
|
| 27 |
|
| 28 |
CodeAstra-7b significantly outperforms existing models in vulnerability detection accuracy. Here's a comparison table:
|
| 29 |
|
| 30 |
-
|
|
| 31 |
|-------------|--------------|
|
| 32 |
| gpt4o | 88.78
|
| 33 |
| CodeAstra-7b| 83.00 |
|
|
|
|
| 27 |
|
| 28 |
CodeAstra-7b significantly outperforms existing models in vulnerability detection accuracy. Here's a comparison table:
|
| 29 |
|
| 30 |
+
|Model | Accuracy (%) |
|
| 31 |
|-------------|--------------|
|
| 32 |
| gpt4o | 88.78
|
| 33 |
| CodeAstra-7b| 83.00 |
|