Instructions to use LukeEuser/docvqa_10_unanswerable_questions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LukeEuser/docvqa_10_unanswerable_questions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="LukeEuser/docvqa_10_unanswerable_questions")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("LukeEuser/docvqa_10_unanswerable_questions") model = AutoModelForImageTextToText.from_pretrained("LukeEuser/docvqa_10_unanswerable_questions") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use LukeEuser/docvqa_10_unanswerable_questions with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LukeEuser/docvqa_10_unanswerable_questions" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LukeEuser/docvqa_10_unanswerable_questions", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LukeEuser/docvqa_10_unanswerable_questions
- SGLang
How to use LukeEuser/docvqa_10_unanswerable_questions 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 "LukeEuser/docvqa_10_unanswerable_questions" \ --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": "LukeEuser/docvqa_10_unanswerable_questions", "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 "LukeEuser/docvqa_10_unanswerable_questions" \ --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": "LukeEuser/docvqa_10_unanswerable_questions", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LukeEuser/docvqa_10_unanswerable_questions with Docker Model Runner:
docker model run hf.co/LukeEuser/docvqa_10_unanswerable_questions
- Xet hash:
- 883d1f695e5f785a66c29da7ad5e1dcd62eec4299009c22ed308cff8ffe57284
- Size of remote file:
- 809 MB
- SHA256:
- 25649338c677d14d11c98dfd2d9db0f0c2bb63f747389860f28e7d31528d82bd
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