---
license: apache-2.0
datasets:
- lambada
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- text-generation-inference
- causal-lm
- int8
- tensorrt
- ENOT-AutoDL
---

# INT8 GPT-J 6B

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.

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).

## Metrics:

|   |TensorRT INT8+FP32|torch FP16|torch FP32|
|---|:---:|:---:|:---:|
| **Lambada Acc** |78.46%|79.53%|-|
| **Model size (GB)**  |8.5|12.1|24.2|

### Test environment

* GPU RTX 4090
* CPU 11th Gen Intel(R) Core(TM) i7-11700K
* TensorRT 8.5.3.1
* pytorch 1.13.1+cu116

## Latency:

|Input sequance length|Number of generated tokens|TensorRT INT8+FP32 ms|torch FP16 ms|Acceleration|
|:---:|:---:|:---:|:---:|:---:|
|64|64|1040|1610|1.55|
|64|128|2089|3224|1.54|
|64|256|4236|6479|1.53|
|128|64|1060|1619|1.53|
|128|128|2120|3241|1.53|
|128|256|4296|6510|1.52|
|256|64|1109|1640|1.49|
|256|128|2204|3276|1.49|
|256|256|4443|6571|1.49|

### Test environment

* GPU RTX 4090
* CPU 11th Gen Intel(R) Core(TM) i7-11700K
* TensorRT 8.5.3.1
* pytorch 1.13.1+cu116

## How to use

Example of inference and accuracy test [published on github](https://github.com/ENOT-AutoDL/ENOT-transformers):
```shell
git clone https://github.com/ENOT-AutoDL/ENOT-transformers
```