Instructions to use gghfez/openwebui-title-generator-270m-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gghfez/openwebui-title-generator-270m-gguf with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="gghfez/openwebui-title-generator-270m-gguf")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("gghfez/openwebui-title-generator-270m-gguf", dtype="auto")

llama-cpp-python

How to use gghfez/openwebui-title-generator-270m-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="gghfez/openwebui-title-generator-270m-gguf",
	filename="openwebui-title-generator-270m.bf16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use gghfez/openwebui-title-generator-270m-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf gghfez/openwebui-title-generator-270m-gguf:BF16
# Run inference directly in the terminal:
llama-cli -hf gghfez/openwebui-title-generator-270m-gguf:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf gghfez/openwebui-title-generator-270m-gguf:BF16
# Run inference directly in the terminal:
llama-cli -hf gghfez/openwebui-title-generator-270m-gguf:BF16

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 gghfez/openwebui-title-generator-270m-gguf:BF16
# Run inference directly in the terminal:
./llama-cli -hf gghfez/openwebui-title-generator-270m-gguf:BF16

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 gghfez/openwebui-title-generator-270m-gguf:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf gghfez/openwebui-title-generator-270m-gguf:BF16

Use Docker

docker model run hf.co/gghfez/openwebui-title-generator-270m-gguf:BF16

LM Studio
Jan

vLLM

How to use gghfez/openwebui-title-generator-270m-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gghfez/openwebui-title-generator-270m-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gghfez/openwebui-title-generator-270m-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/gghfez/openwebui-title-generator-270m-gguf:BF16

SGLang

How to use gghfez/openwebui-title-generator-270m-gguf with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "gghfez/openwebui-title-generator-270m-gguf" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gghfez/openwebui-title-generator-270m-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "gghfez/openwebui-title-generator-270m-gguf" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gghfez/openwebui-title-generator-270m-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use gghfez/openwebui-title-generator-270m-gguf with Ollama:
```
ollama run hf.co/gghfez/openwebui-title-generator-270m-gguf:BF16
```

Unsloth Studio new

How to use gghfez/openwebui-title-generator-270m-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 gghfez/openwebui-title-generator-270m-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 gghfez/openwebui-title-generator-270m-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for gghfez/openwebui-title-generator-270m-gguf to start chatting

Docker Model Runner
How to use gghfez/openwebui-title-generator-270m-gguf with Docker Model Runner:
```
docker model run hf.co/gghfez/openwebui-title-generator-270m-gguf:BF16
```

Lemonade

How to use gghfez/openwebui-title-generator-270m-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gghfez/openwebui-title-generator-270m-gguf:BF16

Run and chat with the model

lemonade run user.openwebui-title-generator-270m-gguf-BF16

List all available models

lemonade list

OpenWebUI Title Generator - Gemma 270M

A fine-tuned Gemma 270M model specialized for generating concise, emoji-enhanced titles for chat conversations. Use this to avoid wasting API credits or wiping out the llama.cpp KV cache after the first message.

Model Description

This model was fine-tuned on 8,900 examples of chat conversation title generation tasks. It takes chat history as input and outputs a JSON-formatted title with 3-5 words and relevant emojis.

Intended Use

Generate titles for chat conversations in OpenWebUI
Summarize conversation themes quickly
Create engaging, emoji-enhanced titles

Performance

Fast inference suitable for real-time title generation
Lightweight at 270M parameters
Consistent JSON output format

Usage

Set this as the "Task Model" in OpenWebUI.

Settings -> Admin -> Interface

Prompt format

The default OpenWebUI prompt format:

### Task:
Generate a concise, 3-5 word title with an emoji summarizing the chat history.
### Guidelines:
- The title should clearly represent the main theme or subject of the conversation.
- Use emojis that enhance understanding of the topic, but avoid quotation marks or special formatting.
- Write the title in the chat's primary language; default to English if multilingual.
- Prioritize accuracy over excessive creativity; keep it clear and simple.
### Output:
JSON format: { "title": "your concise title here" }
### Examples:
- { "title": "📉 Stock Market Trends" },
- { "title": "🍪 Perfect Chocolate Chip Recipe" },
- { "title": "Evolution of Music Streaming" },
- { "title": "Remote Work Productivity Tips" },
- { "title": "Artificial Intelligence in Healthcare" },
- { "title": "🎮 Video Game Development Insights" }
### Chat History:
<chat_history>
USER: hi
ASSISTANT: Hello! How can I assist you today? 😊
USER: who are you?
ASSISTANT: I’m Gemma, a large language model created by the Gemma team at Google DeepMind. I’m an open-weights model, which means I’m widely available for public use!
</chat_history>

Expected response:

'{"title": "👋 Simple Greeting"}'

Limitations

Optimized specifically for title generation in OpenWebUI
May not perform well in other chat interfaces
Emojis sometimes not placed consistently or may be omitted entirely
Only tested at BF16

Downloads last month: 130

GGUF

Model size

0.3B params

Architecture

gemma3

Hardware compatibility

8-bit

16-bit

Model tree for gghfez/openwebui-title-generator-270m-gguf

Base model

google/gemma-3-270m

Finetuned

gghfez/openwebui-title-generator-270m

Quantized

(2)

this model