Instructions to use ssh1419/indi-deplot-lr-half with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssh1419/indi-deplot-lr-half with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ssh1419/indi-deplot-lr-half")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("ssh1419/indi-deplot-lr-half") model = AutoModelForImageTextToText.from_pretrained("ssh1419/indi-deplot-lr-half") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ssh1419/indi-deplot-lr-half with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ssh1419/indi-deplot-lr-half" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ssh1419/indi-deplot-lr-half", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ssh1419/indi-deplot-lr-half
- SGLang
How to use ssh1419/indi-deplot-lr-half 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 "ssh1419/indi-deplot-lr-half" \ --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": "ssh1419/indi-deplot-lr-half", "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 "ssh1419/indi-deplot-lr-half" \ --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": "ssh1419/indi-deplot-lr-half", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ssh1419/indi-deplot-lr-half with Docker Model Runner:
docker model run hf.co/ssh1419/indi-deplot-lr-half
- Xet hash:
- 58d59f9998c914ff4fe3bb2173789b529691d54ba898ab73aefd9ada0c71e7cd
- Size of remote file:
- 1.13 GB
- SHA256:
- 9bde7f49ce82225dda84b031f958de76e1b35e2fb3f3fb01439bfdf0bbaefc1a
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