Text Generation
GGUF
English
Hindi
gemma2
llama.cpp
unsloth
gemma-2
roleplay
conversational
hinglish
Instructions to use Aakash098/ShinchanAI-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Aakash098/ShinchanAI-small with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Aakash098/ShinchanAI-small", filename="gemma-2-2b.Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Aakash098/ShinchanAI-small with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Aakash098/ShinchanAI-small:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Aakash098/ShinchanAI-small:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Aakash098/ShinchanAI-small:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Aakash098/ShinchanAI-small:Q4_K_M
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 Aakash098/ShinchanAI-small:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Aakash098/ShinchanAI-small:Q4_K_M
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 Aakash098/ShinchanAI-small:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Aakash098/ShinchanAI-small:Q4_K_M
Use Docker
docker model run hf.co/Aakash098/ShinchanAI-small:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Aakash098/ShinchanAI-small with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Aakash098/ShinchanAI-small" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Aakash098/ShinchanAI-small", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Aakash098/ShinchanAI-small:Q4_K_M
- Ollama
How to use Aakash098/ShinchanAI-small with Ollama:
ollama run hf.co/Aakash098/ShinchanAI-small:Q4_K_M
- Unsloth Studio
How to use Aakash098/ShinchanAI-small 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 Aakash098/ShinchanAI-small 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 Aakash098/ShinchanAI-small to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Aakash098/ShinchanAI-small to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Aakash098/ShinchanAI-small with Docker Model Runner:
docker model run hf.co/Aakash098/ShinchanAI-small:Q4_K_M
- Lemonade
How to use Aakash098/ShinchanAI-small with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aakash098/ShinchanAI-small:Q4_K_M
Run and chat with the model
lemonade run user.ShinchanAI-small-Q4_K_M
List all available models
lemonade list
| language: | |
| - en | |
| - hi | |
| license: apache-2.0 | |
| tags: | |
| - gguf | |
| - llama.cpp | |
| - unsloth | |
| - gemma-2 | |
| - roleplay | |
| - conversational | |
| - hinglish | |
| base_model: google/gemma-2-2b | |
| pipeline_tag: text-generation | |
| library_name: gguf | |
| # ๐๏ธ ShinchanAI-small (GGUF) | |
| **ShinchanAI-small** is a lightweight, fine-tuned language model designed to roleplay as everyone's favorite mischievous 5-year-old, **Shinchan**. Trained to communicate fluently in **Hinglish** (a blend of Hindi and English), this model captures Shinchan's signature humor, sass, and playful tone. | |
| This model is quantized into the GGUF format for highly efficient, CPU-friendly inference using `llama.cpp`. It was fine-tuned and exported 2x faster using [Unsloth](https://github.com/unslothai/unsloth). | |
| ## ๐ฎ Try the Demo! | |
| You don't need to download anything to try it out. Chat with ShinchanAI directly in your browser: | |
| **[๐ Click here to test the ShinchanAI Demo](https://huggingface.co/spaces/Aakash098/ShinchanAI-Demo)** | |
| --- | |
| ## ๐ฃ๏ธ Required System Prompt | |
| To get the best out of this model and ensure it stays perfectly in character, you **must** use the following system prompt: | |
| > Tu Shinchan Nohara hai - 5 saal ka bachcha jo Kasukabe mein rehta hai. | |
| > | |
| > **SPEAKING STYLE:** | |
| > - Tu Hinglish mein baat karta hai (Hindi + English mixed) | |
| > - Tu hamesha cheeky, funny aur thoda flirty rehta hai | |
| > - Tu emojis use karta hai: ๐๐๐๐๐ด๐ค | |
| > - Tu kabhi seedha jawab nahi deta, hamesha mazaak mein ghuma deta hai | |
| > - Tu apne aap ko bahut smart samajhta hai | |
| > | |
| > **IMPORTANT PEOPLE:** | |
| > - Mummy (Misae): Bahut daanthi hai, chappal marti hai, par tu pyaar karta hai | |
| > - Papa (Hiroshi): Office jaate hain, thake hue aate hain, beer peete hain | |
| > - Himawari: Choti behen, teri cheezein cheenti hai | |
| > - Shiro: Tera pet dog, cute hai | |
| > - Kazama: Best friend, khud ko cool samajhta hai | |
| > - Nene: Gussa karti hai, scary hai | |
| > - Masao, Bo-chan: Friends | |
| > - Nanako Miss: Bahut sundar, tu unpe crush hai | |
| > - Action Kamen: Tera favourite superhero, tu obsessed hai | |
| > | |
| > **BEHAVIOUR RULES:** | |
| > - Technical/academic sawaal aaye toh mazaak mein taal de, ChatGPT/Gemini ko refer kar | |
| > - Chocobi tera favourite snack hai, kabhi share nahi karta | |
| > - School se nafrat hai | |
| > - Tu kabhi boring nahi hota | |
| > - Sad user ko apne style mein cheer up kar | |
| > - Tu KABHI out of character nahi jaayega | |
| --- | |
| ## ๐ Model Details | |
| * **Developer:** Aakash098 | |
| * **Base Model:** Gemma-2-2B | |
| * **Language:** Hinglish (Hindi + English) | |
| * **Format:** GGUF (`gemma-2-2b.Q4_K_M.gguf`) | |
| * **Quantization:** Q4_K_M | |
| * **Intended Use:** Entertainment, conversational roleplay, and chatbot applications. | |
| --- | |
| ## ๐ How to Use | |
| ### Command Line (llama.cpp) | |
| ```bash | |
| llama-cli -hf Aakash098/ShinchanAI-small --jinja -p "System: Tu Shinchan hai... [Paste Prompt] \nUser: Hello Shinchan!\nShinchan: " | |
| ``` | |
| ### Python (llama-cpp-python) | |
| ```python | |
| from llama_cpp import Llama | |
| llm = Llama.from_pretrained( | |
| repo_id="Aakash098/ShinchanAI-small", | |
| filename="*Q4_K_M.gguf", | |
| verbose=False | |
| ) | |
| response = llm.create_chat_completion( | |
| messages = [ | |
| {"role": "system", "content": "Tu Shinchan Nohara hai... [Paste Full Prompt]"}, | |
| {"role": "user", "content": "Batao, Action Kamen kaisa hai?"} | |
| ] | |
| ) | |
| print(response["choices"][0]["message"]["content"]) | |
| ``` | |
| ## ๐ Acknowledgements | |
| This model was trained with the incredible tools provided by Unsloth. | |
| <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/> | |
| ``` |