Instructions to use Arivukkarasu/TinyLlama-1.1B-Chat-GGUF 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 Arivukkarasu/TinyLlama-1.1B-Chat-GGUF 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 Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf Arivukkarasu/TinyLlama-1.1B-Chat-GGUF: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 Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Arivukkarasu/TinyLlama-1.1B-Chat-GGUF: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 Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M
Use Docker
docker model run hf.co/Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Arivukkarasu/TinyLlama-1.1B-Chat-GGUF with Ollama:
ollama run hf.co/Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Arivukkarasu/TinyLlama-1.1B-Chat-GGUF with Docker Model Runner:
docker model run hf.co/Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M
- Lemonade
How to use Arivukkarasu/TinyLlama-1.1B-Chat-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.TinyLlama-1.1B-Chat-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
How to use from
LemonadeRun and chat with the model
lemonade run user.TinyLlama-1.1B-Chat-GGUF-Q4_K_MList all available models
lemonade listQuick Links
TinyLlama-1.1B-Chat - Q4_K_M GGUF
This is a quantized GGUF version of TinyLlama/TinyLlama-1.1B-Chat, quantized to Q4_K_M using llama.cpp's quantization tool.
Model Info
- Base model: TinyLlama-1.1B-Chat
- Quantization: Q4_K_M
- Format: GGUF (compatible with llama.cpp and llama-cpp-python)
- Size: ~500 MB
- Use case: Efficient CPU inference for chat and assistant use-cases
π¦ Files
TinyLlama-1.1B-Chat-Q4_K_M.gguf: The quantized model
How to Use (with llama-cpp-python)
from llama_cpp import Llama
llm = Llama(model_path="TinyLlama-1.1B-Chat-Q4_K_M.gguf")
output = llm("Who are you?", max_tokens=128)
print(output)
Credits
- Original model: TinyLlama/TinyLlama-1.1B-Chat
- Quantized with: llama.cpp
- Downloads last month
- 25
Hardware compatibility
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Base model
TinyLlama/TinyLlama-1.1B-Chat-v1.0
Pull the model
# Download Lemonade from https://lemonade-server.ai/lemonade pull Arivukkarasu/TinyLlama-1.1B-Chat-GGUF:Q4_K_M