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ENOT-AutoDL
/
gpt2-tensorrt

Text Generation
Transformers
ONNX
TensorRT
English
text-generation-inference
causal-lm
int8
ENOT-AutoDL
Model card Files Files and versions
xet
Community
1

Instructions to use ENOT-AutoDL/gpt2-tensorrt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ENOT-AutoDL/gpt2-tensorrt with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="ENOT-AutoDL/gpt2-tensorrt")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("ENOT-AutoDL/gpt2-tensorrt", dtype="auto")
  • TensorRT

    How to use ENOT-AutoDL/gpt2-tensorrt with TensorRT:

    # No code snippets available yet for this library.
    
    # To use this model, check the repository files and the library's documentation.
    
    # Want to help? PRs adding snippets are welcome at:
    # https://github.com/huggingface/huggingface.js
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use ENOT-AutoDL/gpt2-tensorrt with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "ENOT-AutoDL/gpt2-tensorrt"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "ENOT-AutoDL/gpt2-tensorrt",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/ENOT-AutoDL/gpt2-tensorrt
  • SGLang

    How to use ENOT-AutoDL/gpt2-tensorrt 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 "ENOT-AutoDL/gpt2-tensorrt" \
        --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": "ENOT-AutoDL/gpt2-tensorrt",
    		"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 "ENOT-AutoDL/gpt2-tensorrt" \
            --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": "ENOT-AutoDL/gpt2-tensorrt",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use ENOT-AutoDL/gpt2-tensorrt with Docker Model Runner:

    docker model run hf.co/ENOT-AutoDL/gpt2-tensorrt
gpt2-tensorrt
13.2 GB
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  • 2 contributors
History: 3 commits
ivkalgin's picture
ivkalgin
Update README.md (#1)
08766db almost 3 years ago
  • .gitattributes
    1.52 kB
    added trt compatible gpt2-xl onnx almost 3 years ago
  • README.md
    1.41 kB
    Update README.md (#1) almost 3 years ago
  • gpt2-xl-i8.data
    6.61 GB
    xet
    added trt compatible gpt2-xl onnx almost 3 years ago
  • gpt2-xl-i8.onnx
    2.79 MB
    xet
    added trt compatible gpt2-xl onnx almost 3 years ago
  • gpt2-xl.data
    6.6 GB
    xet
    added trt compatible gpt2-xl onnx almost 3 years ago
  • gpt2-xl.onnx
    2.3 MB
    xet
    added trt compatible gpt2-xl onnx almost 3 years ago