Instructions to use L33tcode/llama-3-8b-CEH-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use L33tcode/llama-3-8b-CEH-gguf with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("L33tcode/llama-3-8b-CEH-gguf", dtype="auto")

llama-cpp-python

How to use L33tcode/llama-3-8b-CEH-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="L33tcode/llama-3-8b-CEH-gguf",
	filename="llama-3-CEH-q3_k_s.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use L33tcode/llama-3-8b-CEH-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf L33tcode/llama-3-8b-CEH-gguf:Q3_K_S
# Run inference directly in the terminal:
llama-cli -hf L33tcode/llama-3-8b-CEH-gguf:Q3_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf L33tcode/llama-3-8b-CEH-gguf:Q3_K_S
# Run inference directly in the terminal:
llama-cli -hf L33tcode/llama-3-8b-CEH-gguf:Q3_K_S

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 L33tcode/llama-3-8b-CEH-gguf:Q3_K_S
# Run inference directly in the terminal:
./llama-cli -hf L33tcode/llama-3-8b-CEH-gguf:Q3_K_S

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 L33tcode/llama-3-8b-CEH-gguf:Q3_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf L33tcode/llama-3-8b-CEH-gguf:Q3_K_S

Use Docker

docker model run hf.co/L33tcode/llama-3-8b-CEH-gguf:Q3_K_S

LM Studio
Jan
Ollama
How to use L33tcode/llama-3-8b-CEH-gguf with Ollama:
```
ollama run hf.co/L33tcode/llama-3-8b-CEH-gguf:Q3_K_S
```

Unsloth Studio new

How to use L33tcode/llama-3-8b-CEH-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 L33tcode/llama-3-8b-CEH-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 L33tcode/llama-3-8b-CEH-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for L33tcode/llama-3-8b-CEH-gguf to start chatting

Docker Model Runner
How to use L33tcode/llama-3-8b-CEH-gguf with Docker Model Runner:
```
docker model run hf.co/L33tcode/llama-3-8b-CEH-gguf:Q3_K_S
```

Lemonade

How to use L33tcode/llama-3-8b-CEH-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull L33tcode/llama-3-8b-CEH-gguf:Q3_K_S

Run and chat with the model

lemonade run user.llama-3-8b-CEH-gguf-Q3_K_S

List all available models

lemonade list

Model Card for (llama-3-CEH) LLama3-CyberSec (GGUF)

[]

Model Details

Developed by: L33tcode
License: apache-2.0
Fine-tuned from model: cognitivecomputations/dolphin-2.9-llama3-8b
Model Format: GGUF
Training Data: Datasets of cybersecurity methodologies and codes

Model Description

(llama-3-CEH) LLama3-CyberSec (GGUF) is a fine-tuned version of the LLama3 language model, specifically adapted for cybersecurity applications. The model leverages the GGUF format to optimize performance and efficiency. Fine-tuned using Unsloth and Huggingface's TRL library, this model was trained 2x faster to effectively address tasks related to identifying vulnerabilities, analyzing security protocols, and understanding complex cybersecurity concepts.

Intended Use

(llama-3-CEH) LLama3-CyberSec (GGUF) is intended for use by cybersecurity professionals and researchers to:

Identify and analyze potential security vulnerabilities.
Understand and implement various cybersecurity methodologies.
Analyze code for security flaws and potential exploits.
Generate reports on security findings and best practices.

Limitations and Risks

Uncensored Nature

This model is uncensored, meaning it can generate content that might be considered unethical or harmful. Users must exercise caution and ethical judgment when using this model. It is crucial to use the model responsibly and report any identified vulnerabilities to the relevant authorities or organizations instead of exploiting them.

Ethical Use

Responsibility: Users are fully responsible for any outcomes resulting from the use of this model. The creators of LLama3-CyberSec (GGUF) are not liable for any harm or damage caused.
Security Reporting: Identified vulnerabilities or bugs should be reported to the affected organization or appropriate authority to improve security.

Recommendations for Use

Ethical Hacking and Security Testing: Use the model to ethically find and report vulnerabilities.
Education and Training: Employ the model for educating and training individuals in cybersecurity practices.
Research and Development: Utilize the model for advancing cybersecurity research and improving existing measures.

Future Work

Future versions of (llama-3-CEH) LLama3-CyberSec (GGUF) may include:

Enhanced filtering to prevent the generation of unethical or harmful content.
Additional training data covering more cybersecurity aspects.
Improved guidance and documentation for responsible use.

Disclaimer

(llama-3-CEH) LLama3-CyberSec (GGUF) is provided "as is" without any warranties or guarantees. Use this model at your own risk and comply with all applicable laws and regulations. The developers disclaim any liability for damage or harm resulting from its use.

By using (llama-3-CEH) LLama3-CyberSec (GGUF), you agree to these terms and commit to using the model responsibly and ethically.

For more information on responsible use and best practices in cybersecurity.

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GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

3-bit

View +1 variant

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