Instructions to use ChayanM/Image_Captioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChayanM/Image_Captioner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ChayanM/Image_Captioner")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("ChayanM/Image_Captioner") model = AutoModelForImageTextToText.from_pretrained("ChayanM/Image_Captioner") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ChayanM/Image_Captioner with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ChayanM/Image_Captioner" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ChayanM/Image_Captioner", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ChayanM/Image_Captioner
- SGLang
How to use ChayanM/Image_Captioner 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 "ChayanM/Image_Captioner" \ --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": "ChayanM/Image_Captioner", "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 "ChayanM/Image_Captioner" \ --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": "ChayanM/Image_Captioner", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ChayanM/Image_Captioner with Docker Model Runner:
docker model run hf.co/ChayanM/Image_Captioner
- Xet hash:
- fe016d42283955667a2646f4d45f55ca7985f1765f3fa1aa1316d01acf1869fb
- Size of remote file:
- 958 MB
- SHA256:
- 0bc740506bcb22a1bb7e5f72070b7ee8ee6aab692e13c32f35fc13070e77ab94
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