Instructions to use PyThaGo/LLMLit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PyThaGo/LLMLit with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="PyThaGo/LLMLit",
	filename="LLMLit-0.2-8B-Instruct.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use PyThaGo/LLMLit 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 PyThaGo/LLMLit
# Run inference directly in the terminal:
llama cli -hf PyThaGo/LLMLit

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf PyThaGo/LLMLit
# Run inference directly in the terminal:
llama cli -hf PyThaGo/LLMLit

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 PyThaGo/LLMLit
# Run inference directly in the terminal:
./llama-cli -hf PyThaGo/LLMLit

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 PyThaGo/LLMLit
# Run inference directly in the terminal:
./build/bin/llama-cli -hf PyThaGo/LLMLit

Use Docker

docker model run hf.co/PyThaGo/LLMLit

LM Studio
Jan
Ollama
How to use PyThaGo/LLMLit with Ollama:
```
ollama run hf.co/PyThaGo/LLMLit
```

Unsloth Studio

How to use PyThaGo/LLMLit 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 PyThaGo/LLMLit 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 PyThaGo/LLMLit to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for PyThaGo/LLMLit to start chatting

How to use PyThaGo/LLMLit with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf PyThaGo/LLMLit

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "PyThaGo/LLMLit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use PyThaGo/LLMLit with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf PyThaGo/LLMLit

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default PyThaGo/LLMLit

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use PyThaGo/LLMLit with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf PyThaGo/LLMLit

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "PyThaGo/LLMLit" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use PyThaGo/LLMLit with Docker Model Runner:
```
docker model run hf.co/PyThaGo/LLMLit
```

Lemonade

How to use PyThaGo/LLMLit with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull PyThaGo/LLMLit

Run and chat with the model

lemonade run user.LLMLit-{{QUANT_TAG}}

List all available models

lemonade list

Cristian Sas commited on Jan 30, 2025

Commit

070f783

verified ·

1 Parent(s): 913e955

Update README.md

Browse files

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README.md +15 -0

README.md CHANGED Viewed

@@ -262,7 +262,22 @@ print(response['message']['content'])
 🔗 **Mai multe detalii:** [LLMLit on Hugging Face](https://huggingface.co/LLMLit) 🚀
 ![Civis3.png](https://cdn-uploads.huggingface.co/production/uploads/6769b18893c0c9156b8265d5/pZch1_YVa6Ixc3d_eYxBR.png)

 🔗 **Mai multe detalii:** [LLMLit on Hugging Face](https://huggingface.co/LLMLit) 🚀
+---
+### **Coming Soon! 🚀**
+**Noua funcționalitate** va fi disponibilă curând! Fii pregătit să explorezi opțiuni personalizate pentru aplicațiile tale. Iată o privire asupra parametrilor ce urmează să fie integrați:
+| Parametru           | Descriere                                   | Status         | Data estimată |
+|---------------------|--------------------------------------------|----------------|---------------|
+| **Low-Code Builder** | Construiește aplicații fără a scrie mult cod | **Coming Soon** | Martie 2025    |
+| **AI Integration**   | Integrare completă cu modelele AI          | **Coming Soon** | Aprilie 2025   |
+| **Voice Control**    | Suport complet pentru comenzi vocale       | **Coming Soon** | Mai 2025       |
+| **RAG Support**      | Generare augmentată prin recuperare        | **Coming Soon** | Iunie 2025     |
+| **Teme si Agenti**      | Theme si Chatbots multi-AI pentru asistență și suport	        | **Coming Soon** | Iunie 2025     |
+🔧 **Rămâi conectat!** Detaliile suplimentare vor fi disponibile foarte curând!
+---
 ![Civis3.png](https://cdn-uploads.huggingface.co/production/uploads/6769b18893c0c9156b8265d5/pZch1_YVa6Ixc3d_eYxBR.png)