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--- |
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license: apache-2.0 |
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datasets: |
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- lambada |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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tags: |
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- text-generation-inference |
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- causal-lm |
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- int8 |
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- tensorrt |
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- ENOT-AutoDL |
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--- |
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# INT8 GPT-J 6B |
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GPT-J 6B is a transformer model trained using Ben Wang's [Mesh Transformer JAX](https://github.com/kingoflolz/mesh-transformer-jax/). "GPT-J" refers to the class of model, while "6B" represents the number of trainable parameters. |
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This repository contains GPT-J 6B onnx model suitable for building TensorRT int8+fp32 engines. Quantization of model was performed by the [ENOT-AutoDL](https://pypi.org/project/enot-autodl/) framework. Code for building of TensorRT engines and examples published on [github](https://github.com/ENOT-AutoDL/ENOT-transformers). |
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## Metrics: |
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| |TensorRT INT8+FP32|torch FP16|torch FP32| |
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|---|:---:|:---:|:---:| |
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| **Lambada Acc** |78.46%|79.53%|-| |
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| **Model size (GB)** |8.5|12.1|24.2| |
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### Test environment |
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* GPU RTX 4090 |
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* CPU 11th Gen Intel(R) Core(TM) i7-11700K |
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* TensorRT 8.5.3.1 |
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* pytorch 1.13.1+cu116 |
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## Latency: |
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|Input sequance length|Number of generated tokens|TensorRT INT8+FP32 ms|torch FP16 ms|Acceleration| |
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|:---:|:---:|:---:|:---:|:---:| |
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|64|64|1040|1610|1.55| |
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|64|128|2089|3224|1.54| |
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|64|256|4236|6479|1.53| |
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|128|64|1060|1619|1.53| |
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|128|128|2120|3241|1.53| |
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|128|256|4296|6510|1.52| |
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|256|64|1109|1640|1.49| |
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|256|128|2204|3276|1.49| |
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|256|256|4443|6571|1.49| |
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### Test environment |
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* GPU RTX 4090 |
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* CPU 11th Gen Intel(R) Core(TM) i7-11700K |
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* TensorRT 8.5.3.1 |
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* pytorch 1.13.1+cu116 |
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## How to use |
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Example of inference and accuracy test [published on github](https://github.com/ENOT-AutoDL/ENOT-transformers): |
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```shell |
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git clone https://github.com/ENOT-AutoDL/ENOT-transformers |
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``` |
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