- Libraries
- llama-cpp-python
How to use Sakalti/nekomata-7b-gguf with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="Sakalti/nekomata-7b-gguf",
filename="nekomata-7b.Q4_K_M.gguf",
)
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Sakalti/nekomata-7b-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 Sakalti/nekomata-7b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Sakalti/nekomata-7b-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 Sakalti/nekomata-7b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Sakalti/nekomata-7b-gguf:Q4_K_M
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 Sakalti/nekomata-7b-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf Sakalti/nekomata-7b-gguf:Q4_K_M
Use Docker
docker model run hf.co/Sakalti/nekomata-7b-gguf:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use Sakalti/nekomata-7b-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sakalti/nekomata-7b-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "Sakalti/nekomata-7b-gguf",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Use Docker
docker model run hf.co/Sakalti/nekomata-7b-gguf:Q4_K_M
- Ollama
How to use Sakalti/nekomata-7b-gguf with Ollama:
ollama run hf.co/Sakalti/nekomata-7b-gguf:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Sakalti/nekomata-7b-gguf with Docker Model Runner:
docker model run hf.co/Sakalti/nekomata-7b-gguf:Q4_K_M
- Lemonade
How to use Sakalti/nekomata-7b-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull Sakalti/nekomata-7b-gguf:Q4_K_M
Run and chat with the model
lemonade run user.nekomata-7b-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Sakalti/nekomata-7b-gguf", filename="nekomata-7b.Q4_K_M.gguf", )