|
--- |
|
language: en |
|
license: mit |
|
tags: |
|
- exbert |
|
- text-classification |
|
- onnx |
|
- fp16 |
|
- roberta |
|
- optimum |
|
datasets: |
|
- bookcorpus |
|
- wikipedia |
|
base_model: |
|
- openai-community/roberta-large-openai-detector |
|
--- |
|
|
|
# RoBERTa Large OpenAI Detector |
|
|
|
|
|
This model is a FP16 optimized version of [openai-community/roberta-large-openai-detector](https://huggingface.co/openai-community/roberta-large-openai-detector/). It runs exclusively on the GPU. |
|
The speedup compared to the base ONNX and pytorch versions depends chiefly on your GPU's FP16:FP32 ratio. For more comparison benchmarks and sample code of a related model, check here: [https://github.com/joaopn/gpu_benchmark_goemotions](https://github.com/joaopn/gpu_benchmark_goemotions). |
|
|
|
You will need the GPU version of the ONNX Runtime. It can be installed with |
|
|
|
``` |
|
pip install optimum[onnxruntime-gpu] --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/ |
|
``` |
|
|
|
For convenience, this [benchmark repo](https://github.com/joaopn/gpu_benchmark_goemotions) provides an `environment.yml` file to create a conda env with all the requirements. |