Question Answering
Transformers
GGUF
English
gemma
text-generation-inference
unsloth
static-analysis
code-review
conversational
Instructions to use doss1232/CodeGemma-Offensive-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use doss1232/CodeGemma-Offensive-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="doss1232/CodeGemma-Offensive-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("doss1232/CodeGemma-Offensive-GGUF", dtype="auto") - llama-cpp-python
How to use doss1232/CodeGemma-Offensive-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="doss1232/CodeGemma-Offensive-GGUF", filename="unsloth.F16.gguf", )
llm.create_chat_completion( messages = "{\n \"question\": \"What is my name?\",\n \"context\": \"My name is Clara and I live in Berkeley.\"\n}" ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use doss1232/CodeGemma-Offensive-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf doss1232/CodeGemma-Offensive-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf doss1232/CodeGemma-Offensive-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf doss1232/CodeGemma-Offensive-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf doss1232/CodeGemma-Offensive-GGUF:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf doss1232/CodeGemma-Offensive-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf doss1232/CodeGemma-Offensive-GGUF:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf doss1232/CodeGemma-Offensive-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf doss1232/CodeGemma-Offensive-GGUF:F16
Use Docker
docker model run hf.co/doss1232/CodeGemma-Offensive-GGUF:F16
- LM Studio
- Jan
- Ollama
How to use doss1232/CodeGemma-Offensive-GGUF with Ollama:
ollama run hf.co/doss1232/CodeGemma-Offensive-GGUF:F16
- Unsloth Studio new
How to use doss1232/CodeGemma-Offensive-GGUF 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 doss1232/CodeGemma-Offensive-GGUF 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 doss1232/CodeGemma-Offensive-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for doss1232/CodeGemma-Offensive-GGUF to start chatting
- Docker Model Runner
How to use doss1232/CodeGemma-Offensive-GGUF with Docker Model Runner:
docker model run hf.co/doss1232/CodeGemma-Offensive-GGUF:F16
- Lemonade
How to use doss1232/CodeGemma-Offensive-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull doss1232/CodeGemma-Offensive-GGUF:F16
Run and chat with the model
lemonade run user.CodeGemma-Offensive-GGUF-F16
List all available models
lemonade list
llm.create_chat_completion(
messages = "{\n \"question\": \"What is my name?\",\n \"context\": \"My name is Clara and I live in Berkeley.\"\n}"
)Uploaded model
- Developed by: doss1232
- License: apache-2.0
- Finetuned from model : unsloth/codegemma-7b-it-bnb-4bit
This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.
Model info
This model is part of Offensive-Engine, a family of fine-tuned models for code-review, static-analysis and pentesting in general. It is a CodeGemma 9B model fine-tuned to understand code and detect vulnerabilities.
Memory requirement
This model can be used through lmstudio by searching the author's name and install it. It takes about 20GB to download and used 20GB RAM also.
Usage
- Downloads last month
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Hardware compatibility
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16-bit
Model tree for doss1232/CodeGemma-Offensive-GGUF
Base model
unsloth/codegemma-7b-it-bnb-4bit

# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="doss1232/CodeGemma-Offensive-GGUF", filename="unsloth.F16.gguf", )