Text Generation
PEFT
Safetensors
cybersecurity
vulnerability-detection
java
owasp
code-analysis
lora
conversational
Instructions to use dilekmandal/owasp-java-security-qwen2.5-coder-7b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dilekmandal/owasp-java-security-qwen2.5-coder-7b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "dilekmandal/owasp-java-security-qwen2.5-coder-7b-lora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dilekmandal/owasp-java-security-qwen2.5-coder-7b-lora: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/dilekmandal/owasp-java-security-qwen2.5-coder-7b-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://dilekmandal/owasp-java-security-qwen2.5-coder-7b-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/dilekmandal/owasp-java-security-qwen2.5-coder-7b-lora/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 7f13ff1a2b1f57d11f288caba8caee2d7d129580df1db85b4bedc05d095b89a9
- Size of remote file:
- 11.4 MB
- SHA256:
- 913950e4971737031da511cdd1b410daae4566f62eb845b3975bca5a102323d8
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