VulnLLM-R-7B-8bit

VulnLLM-R-7B-8bit

Runs an 8-bit MLX copy of VulnLLM-R-7B for text generation through mlx-lm. Meant for developers who want to try the model locally. The card does not say what it was trained for.

Made by mlx-community on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

About

What it is: This is an 8-bit copy of VulnLLM-R-7B in MLX format, made by the mlx-community group with mlx-lm version 0.30.0. It is a text generation model of about 7.6B parameters, based on UCSB-SURFI/VulnLLM-R-7B. The card does not describe what the original model was trained for, so read that model's page before relying on it.

Who it suits: It suits developers who run language models locally through MLX and want to try this one. People who need documented benchmarks or a stated purpose should look elsewhere.

Industry | Who uses it | How they use it | Example
Software | Developers | Run the quantized copy locally through mlx-lm | Send a test prompt and read the reply
Research | ML researchers | Compare the 8-bit copy with the original model | Load both and compare their answers
Security | Security engineers | Check whether the model fits their own review work, since the card gives no purpose | Try a short code snippet and judge the answer

Anyone who wants a ready chat app with no Python can skip it.

Where to use it: You run it from Python wherever the mlx-lm package installs.

• A Python script, using the code the card provides
• Windows, macOS or Linux, for downloading the files
• Hugging Face, where the model files are hosted

Use case | Who | What they get back
Try the model locally | Developers | A generated reply printed from a short script
Compare with the original | ML researchers | Side-by-side answers from the 8-bit and original models
Test on code questions | Security engineers | Replies they can judge for their own needs

How to set it up: Setup is one package install and a short script.

• Python
• The mlx-lm package

1. Install the mlx-lm package.
2. Optionally fetch the model files yourself with the Hugging Face hub tools.
3. Save the Python code below to a file and run it.

pip install mlx-lm

pip install -U huggingface_hub
hf download mlx-community/VulnLLM-R-7B-8bit

How to use it: Run the script below. It loads the model, wraps your prompt in the chat format when the tokenizer has one, and prints the generated reply.

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/VulnLLM-R-7B-8bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True, return_dict=False,
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Tool | What it does
load | Loads the model and its tokenizer by name
apply_chat_template | Wraps your message in the chat format when the tokenizer has one
generate | Produces the reply from the prompt and prints it

Example: You send the prompt "hello", as the card's script does. The tokenizer turns it into a chat message, the model writes a reply, and the script prints it. Swap in your own question to see how the model answers.

For newcomers and experts: If you are new, install mlx-lm, run the script as it is, and read the reply to "hello". That one run shows the whole loop of loading, prompting and generating.

For someone who knows the field, this is a quantized MLX conversion of a 7.6B model. The card gives no comparison against the original, so run your own checks before using it for real work.

Model files on Hugging Face
mlx-lm loads model and tokenizer
Chat template wraps your prompt
generate writes the reply

Good to know: The record lists the weights at about 30.5 GB in U32 and the language as English.

• License: Apache-2.0
• Cost to run: none named
• Data it reaches: the card's code names no account, files or web service beyond the model download

On Hugging Face, 13 November 2026

• Task: text generation
• Library: mlx
• Parameters: 7.6B
• Weights: about 30.5 GB in U32
• Formats: Safetensors
• Downloads in the last 30 days: 148
• Likes: 4
• License: apache-2.0
• Languages: en
• Based on: UCSB-SURFI/VulnLLM-R-7B
• Tags: safetensors, qwen2, security, vulnerability-detection, code-analysis, reasoning, text-generation, conversational, code, 8-bit

Links

• Model: https://huggingface.co/mlx-community/VulnLLM-R-7B-8bit
• Files: https://huggingface.co/mlx-community/VulnLLM-R-7B-8bit/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download mlx-community/VulnLLM-R-7B-8bit

Then follow the usage in its model card. Nothing in this kit runs by itself.