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

Libraries

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

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gghfez/openwebui-title-generator-270m")
model = AutoModelForCausalLM.from_pretrained("gghfez/openwebui-title-generator-270m")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use gghfez/openwebui-title-generator-270m 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"
# 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",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

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

SGLang

How to use gghfez/openwebui-title-generator-270m 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" \
    --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",
		"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" \
        --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",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use gghfez/openwebui-title-generator-270m with Docker Model Runner:
```
docker model run hf.co/gghfez/openwebui-title-generator-270m
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

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: 69

Safetensors

Model size

0.3B params

Tensor type

BF16

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

Base model

google/gemma-3-270m

Finetuned

(140)

this model

Quantizations

2 models