Instructions to use renierd6/gemma4-cibersecurity-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use renierd6/gemma4-cibersecurity-lora with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("renierd6/gemma4-cibersecurity-lora", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

Unsloth Studio new

How to use renierd6/gemma4-cibersecurity-lora with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for renierd6/gemma4-cibersecurity-lora to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for renierd6/gemma4-cibersecurity-lora to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for renierd6/gemma4-cibersecurity-lora to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="renierd6/gemma4-cibersecurity-lora",
    max_seq_length=2048,
)

gemma4-cibersecurity-lora / processor_config.json

Commit History

Upload model trained with Unsloth

131d583
verified

renierd6 commited on Apr 13

Commit History

Upload model trained with Unsloth 131d583 verified

Upload model trained with Unsloth

131d583
verified