Summarization
Transformers.js
ONNX
Safetensors
GGUF
English
t5
text2text-generation
llama
title-generation
distillation
tiny-model
edge
cpu
Instructions to use Cyronius/titler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Cyronius/titler with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('summarization', 'Cyronius/titler'); - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Cyronius/titler 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 Cyronius/titler:Q4_K_M # Run inference directly in the terminal: llama cli -hf Cyronius/titler:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Cyronius/titler:Q4_K_M # Run inference directly in the terminal: llama cli -hf Cyronius/titler:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf Cyronius/titler:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf Cyronius/titler:Q4_K_M
Use Docker
docker model run hf.co/Cyronius/titler:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use Cyronius/titler with Ollama:
ollama run hf.co/Cyronius/titler:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Cyronius/titler with Docker Model Runner:
docker model run hf.co/Cyronius/titler:Q4_K_M
- Lemonade
How to use Cyronius/titler with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Cyronius/titler:Q4_K_M
Run and chat with the model
lemonade run user.titler-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 1,508 Bytes
e154c80 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # titler-v3-q4_k_m.gguf
A 5.84M-parameter Llama model (8 layers, 4,352-token vocabulary), quantized to Q4_K_M. It turns a prompt into a short title.
## Training data
Prompts only (no model replies) came from these public datasets. Titles for them were written by Qwen3-14B
(Apache-2.0) and, for a few thousand rows, by OpenAI's gpt-6-luna. The general-text stage used FineWeb-Edu.
| Dataset | License | Note |
|---|---|---|
| [allenai/WildChat-1M](https://huggingface.co/datasets/allenai/WildChat-1M), [WildChat-4.8M](https://huggingface.co/datasets/allenai/WildChat-4.8M) | ODC-BY 1.0 | Attribution: WildChat, Allen Institute for AI. |
| [lmsys/chatbot_arena_conversations](https://huggingface.co/datasets/lmsys/chatbot_arena_conversations) | CC-BY-4.0 for user prompts | Only the user prompts were used (the model replies are CC-BY-NC-4.0). |
| [lmsys/lmsys-chat-1m](https://huggingface.co/datasets/lmsys/lmsys-chat-1m) | LMSYS-Chat-1M Dataset License Agreement | Allows research and commercial use and training models. It forbids passing on the dataset. This repository contains no part of the dataset. |
| [OpenAssistant/oasst2](https://huggingface.co/datasets/OpenAssistant/oasst2) | Apache-2.0 | |
| [HuggingFaceFW/fineweb-edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) | ODC-BY 1.0 | General-text stage. |
Rows about sexual content with minors were removed before training.
This file records what the dataset pages say on 2026-10-19. It is not legal advice.
|