Instructions to use dxoth1nh/poc-llama-cpp-chat-template-recursion-dos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dxoth1nh/poc-llama-cpp-chat-template-recursion-dos with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="dxoth1nh/poc-llama-cpp-chat-template-recursion-dos",
	filename="macro-recursion.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use dxoth1nh/poc-llama-cpp-chat-template-recursion-dos with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dxoth1nh/poc-llama-cpp-chat-template-recursion-dos
# Run inference directly in the terminal:
llama cli -hf dxoth1nh/poc-llama-cpp-chat-template-recursion-dos

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dxoth1nh/poc-llama-cpp-chat-template-recursion-dos
# Run inference directly in the terminal:
llama cli -hf dxoth1nh/poc-llama-cpp-chat-template-recursion-dos

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 dxoth1nh/poc-llama-cpp-chat-template-recursion-dos
# Run inference directly in the terminal:
./llama-cli -hf dxoth1nh/poc-llama-cpp-chat-template-recursion-dos

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 dxoth1nh/poc-llama-cpp-chat-template-recursion-dos
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dxoth1nh/poc-llama-cpp-chat-template-recursion-dos

Use Docker

docker model run hf.co/dxoth1nh/poc-llama-cpp-chat-template-recursion-dos

LM Studio
Jan
Ollama
How to use dxoth1nh/poc-llama-cpp-chat-template-recursion-dos with Ollama:
```
ollama run hf.co/dxoth1nh/poc-llama-cpp-chat-template-recursion-dos
```

Unsloth Studio

How to use dxoth1nh/poc-llama-cpp-chat-template-recursion-dos 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 dxoth1nh/poc-llama-cpp-chat-template-recursion-dos 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 dxoth1nh/poc-llama-cpp-chat-template-recursion-dos to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for dxoth1nh/poc-llama-cpp-chat-template-recursion-dos to start chatting

Atomic Chat new
Docker Model Runner
How to use dxoth1nh/poc-llama-cpp-chat-template-recursion-dos with Docker Model Runner:
```
docker model run hf.co/dxoth1nh/poc-llama-cpp-chat-template-recursion-dos
```

Lemonade

How to use dxoth1nh/poc-llama-cpp-chat-template-recursion-dos with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull dxoth1nh/poc-llama-cpp-chat-template-recursion-dos

Run and chat with the model

lemonade run user.poc-llama-cpp-chat-template-recursion-dos-{{QUANT_TAG}}

List all available models

lemonade list

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Gated security PoC artifact

Proof-of-concept artifact for a responsibly disclosed model file vulnerability report.

Format: GGUF (.gguf)

This repository is for defensive validation and triage only. It is not a usable model. Do not request access unless you are the assigned reviewer.

Contents:

macro-recursion.gguf: crafted artifact
replay_llama_completion.py: bounded reproduction script for llama-completion
build-meta.json: local validation metadata and hashes

Expected reviewer flow:

Download the artifact into an isolated environment.
Build or provide llama-completion from the tested llama.cpp revision.
Run:

python3 replay_llama_completion.py --completion-bin /path/to/llama-completion

Expected result:

the process terminates with SIGSEGV (returncode 139) while handling the embedded chat template.

Downloads last month: 2

GGUF

Model size

293k params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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