Instructions to use egeozsoy/MM-OR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egeozsoy/MM-OR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="egeozsoy/MM-OR")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("egeozsoy/MM-OR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use egeozsoy/MM-OR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "egeozsoy/MM-OR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "egeozsoy/MM-OR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/egeozsoy/MM-OR
- SGLang
How to use egeozsoy/MM-OR 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 "egeozsoy/MM-OR" \ --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": "egeozsoy/MM-OR", "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 "egeozsoy/MM-OR" \ --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": "egeozsoy/MM-OR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use egeozsoy/MM-OR with Docker Model Runner:
docker model run hf.co/egeozsoy/MM-OR
Download 4D-OR_panoptic_segmentations.zip from egeozsoy/MM-OR: direct link, hf CLI and curl.
- Browser
- Download file 159 MB
-
https://huggingface.co/egeozsoy/MM-OR/resolve/main/4D-OR_panoptic_segmentations.zip
- Command line
-
hf download hf://egeozsoy/MM-OR/4D-OR_panoptic_segmentations.zip
-
curl -L -o 4D-OR_panoptic_segmentations.zip https://huggingface.co/egeozsoy/MM-OR/resolve/main/4D-OR_panoptic_segmentations.zip
159 MB
- Xet hash:
- d5bad7c031ae5f7fbad6c5784b4e44f66d0140181439836da2c13281c7df4238
- Size of remote file:
- 159 MB
- SHA256:
- 8d297237438cba563a28aa6eaa0ceebde46bb23c9abdca3d5f1e69170fea8930
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