Libraries llama-cpp-python How to use ngxson/tinyllama_split_test with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="ngxson/tinyllama_split_test",
filename="stories15M-q8_0-00001-of-00003.gguf",
)
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output) Notebooks Google Colab Kaggle Local Apps llama.cpp How to use ngxson/tinyllama_split_test with llama.cpp:
Install from brew brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ngxson/tinyllama_split_test:Q8_0
# Run inference directly in the terminal:
llama-cli -hf ngxson/tinyllama_split_test:Q8_0 Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ngxson/tinyllama_split_test:Q8_0
# Run inference directly in the terminal:
llama-cli -hf ngxson/tinyllama_split_test:Q8_0 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 ngxson/tinyllama_split_test:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf ngxson/tinyllama_split_test:Q8_0 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 ngxson/tinyllama_split_test:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ngxson/tinyllama_split_test:Q8_0 Use Docker docker model run hf.co/ngxson/tinyllama_split_test:Q8_0 LM Studio Jan Ollama How to use ngxson/tinyllama_split_test with Ollama:
ollama run hf.co/ngxson/tinyllama_split_test:Q8_0 Unsloth Studio new How to use ngxson/tinyllama_split_test 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 ngxson/tinyllama_split_test 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 ngxson/tinyllama_split_test to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ngxson/tinyllama_split_test to start chatting Docker Model Runner How to use ngxson/tinyllama_split_test with Docker Model Runner:
docker model run hf.co/ngxson/tinyllama_split_test:Q8_0 Lemonade How to use ngxson/tinyllama_split_test with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull ngxson/tinyllama_split_test:Q8_0 Run and chat with the model lemonade run user.tinyllama_split_test-Q8_0 List all available models lemonade list 
Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ngxson/tinyllama_split_test to start chatting