Convert Transformers to ONNX with Hugging Face Optimum
What Happened
Convert Transformers to ONNX with Hugging Face Optimum
Fordel's Take
converting transformers to onnx with optimum is smart, but it's really about deployment friction. trying to run massive transformer models in production is a nightmare unless you optimize the graph. onnx gives us the standardized format we need to move models off the experimental setup and onto actual inference hardware.
this isn't about the conversion itself; it's about quantization and graph optimization. we need to get the model down to the bare minimum size and computational cost without losing fidelity. if you can't run it fast enough, it doesn't matter if it's mathematically perfect.
What To Do
Prioritize 4-bit quantization and use onnxruntime for high-performance, low-latency inference deployment.
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