Instructions to use remyxai/SpaceLLaVA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use remyxai/SpaceLLaVA with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="remyxai/SpaceLLaVA")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("remyxai/SpaceLLaVA")
model = AutoModelForCausalLM.from_pretrained("remyxai/SpaceLLaVA", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use remyxai/SpaceLLaVA 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 remyxai/SpaceLLaVA:F16
# Run inference directly in the terminal:
llama cli -hf remyxai/SpaceLLaVA:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf remyxai/SpaceLLaVA:F16
# Run inference directly in the terminal:
llama cli -hf remyxai/SpaceLLaVA:F16

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 remyxai/SpaceLLaVA:F16
# Run inference directly in the terminal:
./llama-cli -hf remyxai/SpaceLLaVA:F16

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 remyxai/SpaceLLaVA:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf remyxai/SpaceLLaVA:F16

Use Docker

docker model run hf.co/remyxai/SpaceLLaVA:F16

LM Studio
Jan

vLLM

How to use remyxai/SpaceLLaVA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "remyxai/SpaceLLaVA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "remyxai/SpaceLLaVA",
		"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"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/remyxai/SpaceLLaVA:F16

SGLang

How to use remyxai/SpaceLLaVA with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "remyxai/SpaceLLaVA" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "remyxai/SpaceLLaVA",
		"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"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "remyxai/SpaceLLaVA" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "remyxai/SpaceLLaVA",
		"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"
						}
					}
				]
			}
		]
	}'

Ollama
How to use remyxai/SpaceLLaVA with Ollama:
```
ollama run hf.co/remyxai/SpaceLLaVA:F16
```

Unsloth Studio

How to use remyxai/SpaceLLaVA 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 remyxai/SpaceLLaVA 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 remyxai/SpaceLLaVA to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for remyxai/SpaceLLaVA to start chatting

Docker Model Runner
How to use remyxai/SpaceLLaVA with Docker Model Runner:
```
docker model run hf.co/remyxai/SpaceLLaVA:F16
```

Lemonade

How to use remyxai/SpaceLLaVA with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull remyxai/SpaceLLaVA:F16

Run and chat with the model

lemonade run user.SpaceLLaVA-F16

List all available models

lemonade list

Atomic Chat

SpaceLLaVA / docker /Dockerfile

salma-remyx

Add SpaceLlaVA Triton Server

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	FROM nvcr.io/nvidia/tritonserver:22.11-py3

	WORKDIR /workspace

	RUN apt-get update && apt-get install cmake -y

	RUN pip install --upgrade pip && pip install --upgrade tensorrt

	RUN git clone https://github.com/NVIDIA/TensorRT.git -b main --single-branch \
	&& cd TensorRT \
	&& git submodule update --init --recursive

	ENV TRT_OSSPATH=/workspace/TensorRT
	WORKDIR ${TRT_OSSPATH}

	RUN mkdir -p build \
	&& cd build \
	&& cmake .. -DTRT_OUT_DIR=$PWD/out \
	&& cd plugin \
	&& make -j$(nproc)

	ENV PLUGIN_LIBS="${TRT_OSSPATH}/build/out/libnvinfer_plugin.so"

	WORKDIR /weights
	RUN wget https://huggingface.co/remyxai/SpaceLLaVA/resolve/main/ggml-model-q4_0.gguf
	RUN wget https://huggingface.co/remyxai/SpaceLLaVA/resolve/main/mmproj-model-f16.gguf

	RUN python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
	RUN CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python==0.2.45 --force-reinstall --no-cache-dir

	WORKDIR /models
	COPY ./models/ .

	WORKDIR /workspace
	CMD ["tritonserver", "--model-store=/models"]