Instructions to use SawanStack/gpt2-image-captioning-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SawanStack/gpt2-image-captioning-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SawanStack/gpt2-image-captioning-onnx")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("SawanStack/gpt2-image-captioning-onnx") model = AutoModelForImageTextToText.from_pretrained("SawanStack/gpt2-image-captioning-onnx") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SawanStack/gpt2-image-captioning-onnx with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SawanStack/gpt2-image-captioning-onnx" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SawanStack/gpt2-image-captioning-onnx", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SawanStack/gpt2-image-captioning-onnx
- SGLang
How to use SawanStack/gpt2-image-captioning-onnx 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 "SawanStack/gpt2-image-captioning-onnx" \ --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": "SawanStack/gpt2-image-captioning-onnx", "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 "SawanStack/gpt2-image-captioning-onnx" \ --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": "SawanStack/gpt2-image-captioning-onnx", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SawanStack/gpt2-image-captioning-onnx with Docker Model Runner:
docker model run hf.co/SawanStack/gpt2-image-captioning-onnx
- Xet hash:
- 8f69634598c6cb2e5c3befdcd999e9d09fb473e23f7b08abb5dbb4f710844c8f
- Size of remote file:
- 769 MB
- SHA256:
- 896b39513ced6e7654cc10efd6ef7238d70a5d9c12bed6e20d685cf8ab619c26
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