Instructions to use cyberviser/hancock-v0.3.2-adapter-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cyberviser/hancock-v0.3.2-adapter-v4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3-bnb-4bit") model = PeftModel.from_pretrained(base_model, "cyberviser/hancock-v0.3.2-adapter-v4") - Notebooks
- Google Colab
- Kaggle
Hancock v0.3.2 Adapter v4 (LoRA)
Local QLoRA refresh on glasseye RTX 5070. Init from hancock-v0.3.2-adapter, data hancock_refresh_v4. train_loss ? 1.03, 250 steps.
Prefer cyberviser/hancock-pentest-v4 for detection/hunting.
Developed by: cyberviser / GLASSEYE
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Model tree for cyberviser/hancock-v0.3.2-adapter-v4
Base model
mistralai/Mistral-7B-v0.3 Finetuned
mistralai/Mistral-7B-Instruct-v0.3