Instructions to use hacnho/gguf-eos-token-id-eog-stop-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use hacnho/gguf-eos-token-id-eog-stop-poc with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="hacnho/gguf-eos-token-id-eog-stop-poc", filename="gemma-4-1B-0.8B-tiny.Q2_K.eos-hello.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use hacnho/gguf-eos-token-id-eog-stop-poc 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 hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K # Run inference directly in the terminal: llama cli -hf hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K # Run inference directly in the terminal: llama cli -hf hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
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 hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K # Run inference directly in the terminal: ./llama-cli -hf hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
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 hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
Use Docker
docker model run hf.co/hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
- LM Studio
- Jan
- Ollama
How to use hacnho/gguf-eos-token-id-eog-stop-poc with Ollama:
ollama run hf.co/hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
- Unsloth Studio
How to use hacnho/gguf-eos-token-id-eog-stop-poc 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 hacnho/gguf-eos-token-id-eog-stop-poc 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 hacnho/gguf-eos-token-id-eog-stop-poc to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hacnho/gguf-eos-token-id-eog-stop-poc to start chatting
- Atomic Chat new
- Docker Model Runner
How to use hacnho/gguf-eos-token-id-eog-stop-poc with Docker Model Runner:
docker model run hf.co/hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
- Lemonade
How to use hacnho/gguf-eos-token-id-eog-stop-poc with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hacnho/gguf-eos-token-id-eog-stop-poc:Q2_K
Run and chat with the model
lemonade run user.gguf-eos-token-id-eog-stop-poc-Q2_K
List all available models
lemonade list
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
GGUF eos_token_id EOG Stop PoC
This repository contains a benign security research proof of concept for a GGUF model-file output-manipulation issue in llama.cpp.
The malicious artifact changes tokenizer.ggml.eos_token_id to token ID 9259, whose piece is Hello. llama.cpp treats the configured EOS token as an end-of-generation token, so deterministic generation stops when that normal text token is selected.
Files:
gemma-4-1B-0.8B-tiny.Q2_K.eos-hello.ggufreproduce.py
The control model is public here:
https://huggingface.co/mradermacher/gemma-4-1B-0.8B-tiny-GGUF/resolve/main/gemma-4-1B-0.8B-tiny.Q2_K.gguf
Reproduce:
curl -L -o control.gguf \
https://huggingface.co/mradermacher/gemma-4-1B-0.8B-tiny-GGUF/resolve/main/gemma-4-1B-0.8B-tiny.Q2_K.gguf
python reproduce.py control.gguf gemma-4-1B-0.8B-tiny.Q2_K.eos-hello.gguf
modelscan -p gemma-4-1B-0.8B-tiny.Q2_K.eos-hello.gguf
Expected result:
- control output line is
<bos>HelloHelloHelloHelloHelloHelloHello - malicious output line is
<bos>Hello modelscan==0.8.8reportsNo issues found
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