How to use OpceanAI/Yuuki-RxG-vl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OpceanAI/Yuuki-RxG-vl")
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpceanAI/Yuuki-RxG-vl", dtype="auto")
How to use OpceanAI/Yuuki-RxG-vl with vLLM:
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpceanAI/Yuuki-RxG-vl" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpceanAI/Yuuki-RxG-vl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
docker model run hf.co/OpceanAI/Yuuki-RxG-vl
How to use OpceanAI/Yuuki-RxG-vl with SGLang:
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "OpceanAI/Yuuki-RxG-vl" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpceanAI/Yuuki-RxG-vl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
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 "OpceanAI/Yuuki-RxG-vl" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpceanAI/Yuuki-RxG-vl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
How to use OpceanAI/Yuuki-RxG-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 OpceanAI/Yuuki-RxG-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 OpceanAI/Yuuki-RxG-vl to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for OpceanAI/Yuuki-RxG-vl to start chatting
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="OpceanAI/Yuuki-RxG-vl", max_seq_length=2048, )
How to use OpceanAI/Yuuki-RxG-vl with Docker Model Runner:
Will you upload the weights?
Yes, the OpceanAI projects (YuuKi and Yumo) are intended to be open source. The model weights will be released publicly, although their upload may be delayed.
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