Instructions to use MebinThattil/tiny-llama-q4_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MebinThattil/tiny-llama-q4_0 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 MebinThattil/tiny-llama-q4_0 # Run inference directly in the terminal: llama cli -hf MebinThattil/tiny-llama-q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MebinThattil/tiny-llama-q4_0 # Run inference directly in the terminal: llama cli -hf MebinThattil/tiny-llama-q4_0
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 MebinThattil/tiny-llama-q4_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf MebinThattil/tiny-llama-q4_0
Use Docker
docker model run hf.co/MebinThattil/tiny-llama-q4_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use MebinThattil/tiny-llama-q4_0 with Ollama:
ollama run hf.co/MebinThattil/tiny-llama-q4_0
- Unsloth Desktop
- Docker Model Runner
How to use MebinThattil/tiny-llama-q4_0 with Docker Model Runner:
docker model run hf.co/MebinThattil/tiny-llama-q4_0
- Lemonade
How to use MebinThattil/tiny-llama-q4_0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MebinThattil/tiny-llama-q4_0
Run and chat with the model
lemonade run user.tiny-llama-q4_0-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download chatapp.py from MebinThattil/tiny-llama-q4_0: direct link, hf CLI and curl.
- Browser
- Download file 697 Bytes
-
https://huggingface.co/MebinThattil/tiny-llama-q4_0/resolve/main/chatapp.py
- Command line
-
hf download hf://MebinThattil/tiny-llama-q4_0/chatapp.py
-
curl -L -o chatapp.py https://huggingface.co/MebinThattil/tiny-llama-q4_0/resolve/main/chatapp.py
697 Bytes
| import sys | |
| from llama_cpp import Llama | |
| if len(sys.argv) < 2: | |
| print("Model path not provided as argument") | |
| print("Eg. Usage: $ python chatapp.py path/to/model.gguf") | |
| sys.exit(1) | |
| llm = Llama( | |
| model_path=sys.argv[1], | |
| n_ctx=512, | |
| n_threads=4, | |
| n_gpu_layers=1, | |
| verbose=False | |
| ) | |
| print("Chat with Llama (type 'exit' to quit)\n") | |
| while True: | |
| user_input = input("You: ") | |
| if user_input.lower() in ["exit", "quit"]: break | |
| prompt = f"### Human: {user_input}\n### Assistant:" | |
| output = llm( | |
| prompt, | |
| max_tokens=100, | |
| stop=["###", "### Human:", "\n###"] | |
| ) | |
| response = output["choices"][0]["text"].strip() | |
| print("Bot:", response) | |