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Add Triton + TensorRT-LLM inference example #86
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| input [ | ||
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| name: "text_input" |
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prompt?
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This is only for configuring the shapes and other params. System prompt would have to come directly in the model.py
| #!/usr/bin/env python3 | ||
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| Download HuggingFace model to persistent storage. | ||
| Only downloads if model doesn't already exist. |
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Do you run this with cerebrium run or does it run on deploy?
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I thought about this but I'm also not feeling great on reinstalling packages (once through the docker file and once through toml)
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| for request in requests: |
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This doesn't look that efficient
This example demonstrates how to deploy a high-performance LLM inference server using NVIDIA Triton Inference Server with TensorRT-LLM for optimized GPU inference.
Features:
The deployment uses an A10 GPU and exposes Triton's standard HTTP API on port 8000.