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efficiencyx/Titlewen-GGUF

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

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Model Card

Titlewen-GGUF

Titlewen is a small specialized title-generation model based on Qwen3-0.6B, fine-tuned to turn user messages into short, descriptive conversation titles.

This repository contains the GGUF version intended for lightweight local inference with runtimes such as llama.cpp.

What it does

Titlewen takes an arbitrary user message and produces a concise title describing its main topic.

Examples:

Input	Output
`Hey we are at the coffee shop, do you want anything?`	`Coffee Shop Chat`
`CUDA out of memory. Tried to allocate 20.00 MiB...`	`CUDA Memory Allocation Error`
`how is this possible? rtx 3060...`	`RTX 3060 Performance Analysis`
`Help me make the README a bit better`	`Improving README Clarity`

The model is designed for applications such as:

—automatic chat/conversation naming
—message and thread titles
—support-ticket titles
—compact topic extraction
—short UI labels derived from user input

Model details

—Base model: Qwen/Qwen3-0.6B
—Task: Short title generation
—Architecture: Decoder-only Transformer
—Training method: LoRA fine-tuning
—Training dataset: approximately 20,000 title-generation examples
—Output style: typically 2–6 words
—Format: GGUF
—Primary languages: English