Instructions to use SenseLLM/SpiritSight-Agent-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SenseLLM/SpiritSight-Agent-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SenseLLM/SpiritSight-Agent-8B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SenseLLM/SpiritSight-Agent-8B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SenseLLM/SpiritSight-Agent-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SenseLLM/SpiritSight-Agent-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SenseLLM/SpiritSight-Agent-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SenseLLM/SpiritSight-Agent-8B
- SGLang
How to use SenseLLM/SpiritSight-Agent-8B 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 "SenseLLM/SpiritSight-Agent-8B" \ --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": "SenseLLM/SpiritSight-Agent-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "SenseLLM/SpiritSight-Agent-8B" \ --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": "SenseLLM/SpiritSight-Agent-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SenseLLM/SpiritSight-Agent-8B with Docker Model Runner:
docker model run hf.co/SenseLLM/SpiritSight-Agent-8B
Comparison of Effects
#2
by flymusic - opened
The models you compared seem a bit outdated. Have you considered comparing them with CogAgent-9B-20241220, Microsoft/OmniParser-v2.0, and ShowUI?
The model was trained in July 2024. We will consider updating our work in the future.
感谢你的回复,正在读论文,从数据构成来看基于最新的Qwen2.5-VL训练,可能会有进一步的提升,期待你们的新作