HuggingFaceM4/FineVision
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How to use VatsaDev/sakura-vl with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="VatsaDev/sakura-vl", filename="1b_text_alpha.gguf", )
llm.create_chat_completion(
messages = [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Describe this image in one sentence."
},
{
"type": "image_url",
"image_url": {
"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
}
}
]
}
]
)How to use VatsaDev/sakura-vl with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf VatsaDev/sakura-vl # Run inference directly in the terminal: llama-cli -hf VatsaDev/sakura-vl
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf VatsaDev/sakura-vl # Run inference directly in the terminal: llama-cli -hf VatsaDev/sakura-vl
# 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 VatsaDev/sakura-vl # Run inference directly in the terminal: ./llama-cli -hf VatsaDev/sakura-vl
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 VatsaDev/sakura-vl # Run inference directly in the terminal: ./build/bin/llama-cli -hf VatsaDev/sakura-vl
docker model run hf.co/VatsaDev/sakura-vl
How to use VatsaDev/sakura-vl with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "VatsaDev/sakura-vl"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "VatsaDev/sakura-vl",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Describe this image in one sentence."
},
{
"type": "image_url",
"image_url": {
"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
}
}
]
}
]
}'docker model run hf.co/VatsaDev/sakura-vl
How to use VatsaDev/sakura-vl with Ollama:
ollama run hf.co/VatsaDev/sakura-vl
How to use VatsaDev/sakura-vl with Unsloth Studio:
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 VatsaDev/sakura-vl to start chatting
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 VatsaDev/sakura-vl to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for VatsaDev/sakura-vl to start chatting
How to use VatsaDev/sakura-vl with Pi:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf VatsaDev/sakura-vl
# 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": "VatsaDev/sakura-vl"
}
]
}
}
}# Start Pi in your project directory: pi
How to use VatsaDev/sakura-vl with Hermes Agent:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf VatsaDev/sakura-vl
# 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 VatsaDev/sakura-vl
hermes
How to use VatsaDev/sakura-vl with Docker Model Runner:
docker model run hf.co/VatsaDev/sakura-vl
How to use VatsaDev/sakura-vl with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull VatsaDev/sakura-vl
lemonade run user.sakura-vl-{{QUANT_TAG}}lemonade list
We're not able to determine the quantization variants.
Base model
prism-ml/Bonsai-1.7B-unpacked